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Precise radar pulse detection is the premise of electronic support measures. A constant false alarm rate (CFAR) detection algorithm based on difference of box (DOB) filter is proposed to realise low‐complexity and environment‐adaptive radar pulse detection, and the principle behind the proposed algorithm is revealed. Specifically, the DOB filter is adopted to extract the rising edges and falling edges of radar pulses, and the signal variation law of probability density functions (PDFs) during the process of DOB filter are first theoretically analysed. Based on the derived PDFs, dynamic detection threshold and fixed threshold factor for the proposed CFAR algorithm based on DOB filter are deduced to detect the presence of radar pulses. Furthermore, the closed‐form expression of the detection probability is derived. Simulations and on‐board field programmable gate arrays implementation verify the superiority of the proposed CFAR algorithm based on DOB filter. Simulation results show that the proposed algorithm performs well in detecting various types of pulse signals, the detection probability ≥99% on condition that the signal‐to‐noise ratio ≥3 dB and false alarm probability = 10−8. Moreover, the proposed CFAR algorithm based on DOB filter can deal with both singular pulses and pulse on pulse signals. [ABSTRACT FROM AUTHOR]

In this paper, a power allocation algorithm of dual-function radar–communication system with limited power is proposed to obtain better overall system performance measured by the weighted summation of radar signal to interference plus noise ratio (SINR) and communication channel capacity. First, a power allocation model is established to maximize the radar SINR and communication channel capacity with limited transmitted power. Then, the Karush–Kuhn–Tucker (KKT) conditions are used to solve the optimal objective function under the condition that only radar SINR or communication channel capacity is considered, respectively. Finally, the optimal value is combined with the original model and transformed into a single objective optimization model, and the optimal power is obtained by solving the model through the iterative optimization algorithm. Simulation results show that, compared with other power allocation algorithms, the proposed algorithm can achieve better radar-communication integration performance under the same transmit power. [ABSTRACT FROM AUTHOR]

Radar profiling algorithms are widely used for precipitation‐induced path‐attenuation correction. In this study, we investigate the impact of the four well‐known profiling algorithms on the efficacy of quantitative precipitation estimation retrievals. The first method, named the "simple PhiDP‐based method", distributes precipitation‐induced path attenuation, or PhiDP (differential phase shift), of a rain segment to each radar gate according to radar reflectivity (Zh). The second one is a linear version of the ZPHI method derived from an approximate linear relationship between specific attenuation (Ah) and specific differential phase (KDP). The third one is a nonlinear version of the ZPHI that respects the nonlinearity of the Ah–KDP relationship. The fourth method is inspired from the self‐consistent method of Bringi. The two‐moment normalized raindrop size distribution (DSD) with two variables, scaled drop concentration Nw$$ {N}_{\mathrm{w}} $$ and mean drop diameter Dm$$ {D}_{\mathrm{m}} $$, is used to represent natural variability of DSD. Two configurations are considered: a constant Nw$$ {N}_{\mathrm{w}} $$ over a segment and a variable Nw$$ {N}_{\mathrm{w}} $$ over a segment. The Ah, KDP, and rain intensity R$$ R $$ are estimated by the four profiling algorithms. The sensitivity of each algorithm to radar measurements uncertainty is also investigated. The evaluation of the estimates shows the following. First, for the range‐constant Nw$$ {N}_{\mathrm{w}} $$ situation, the nonlinear ZPHI and the self‐consistent method yield the best estimates if the measurements errors are not considered. However, the nonlinear ZPHI and the self‐consistent method are significantly impacted by the Zh bias and the measurements noises respectively. Second, for the range‐variable Nw$$ {N}_{\mathrm{w}} $$ situation, the self‐consistent method does not have a good performance even when radar measurements are accurate. The performance of the nonlinear ZPHI method is similar to the simple PhiDP‐based method, whereas the latter is immune to the Zh calibration error. These results suggest that the benefit of introducing Nw$$ {N}_{\mathrm{w}} $$ in quantitative precipitation estimation algorithms can be significantly reduced if Nw$$ {N}_{\mathrm{w}} $$ is not constant in reality and/or if the radar measurements are biased and noisy. [ABSTRACT FROM AUTHOR]

Orthogonal time frequency space (OTFS) is a new method technique that supports reliable information transmission in a strong Doppler environment. Aiming at the radar target parameter estimation problem of integration of radar and communication (IRC) based on OTFS, this paper proposes a two‐step radar target parameter estimation algorithm combining maximum likelihood (ML) estimation and gradient descent (GD) principle. Firstly, the echo signal of the OTFS integrated signal is constructed and based on this, the ML estimation model is constructed, and the alternating projection (AP) algorithm is employed to make a rough estimation of the target parameters. Then the rough estimation results of the AP‐ML algorithm are employed as the initial value of the GD algorithm for the fine parameter estimation. Simulation results show that the proposed algorithm has better target parameter estimation performance and resolution while reducing the computational complexity. [ABSTRACT FROM AUTHOR]

It is difficult for a receiver to intercept the signals from a radar system that can emit low probability of intercept (LPI) polyphase coded signals. The traditional Wigner Hough transform (WHT) algorithm requires a large amount of computation and takes a long time to estimate the parameters of the LPI radar polyphase coded signals. To address this problem, an iterative angle search (IAS) algorithm, which when used in combination with the WHT algorithm significantly reduces the computational cost is proposed. When the signal‐to‐noise ratio is in the range of −4 to 20 dB, the carrier frequency, number of subcodes, and number of cycles of the carrier frequency per subcode of five polyphase coded signals, namely, Frank, P1, P2, P3, and P4, are accurately estimated in simulation experiments. Based on the selected IAS algorithm parameters, the estimation accuracy of the proposed method is the same as that of the traditional WHT algorithm. However, the operation time is only 5.14% of that of the traditional method. The IAS algorithm has certain application prospects. Experiments indicate that the proposed algorithm provides excellent performance and can rapidly and accurately estimate the parameters of LPI polyphase codes. [ABSTRACT FROM AUTHOR]

Small‐array high‐frequency surface wave radar (HFSWR) is widely used to monitor maritime targets as it can be used to save on‐land resources. In small‐array HFSWR systems, the main lobe of the receiving angle spectrum is significantly broadened. In complex clutter backgrounds, an extremely wide beam severely influences clutter suppression performance; consequently, targets with a low signal‐to‐clutter ratio (SCR) may be eliminated, or the angle may be barely estimated. This study proposes a space‐time adaptive processing (STAP) algorithm based on hyper beamforming (HBF) to improve the clutter suppression performance of small‐array HFSWR. In addition, HBF can obtain more independent identical distributed training samples than the conventional beamforming; thus, the STAP algorithm can extract the clutter information with high accuracy in the covariance matrix estimation. Moreover, this study combines an efficient STAP algorithm with a joint domain localised (JDL) algorithm to improve clutter suppression. Based on the experimental results, the proposed HBF‐JDL algorithm performs satisfactorily and significantly improves the SCR. Moreover, HBF‐JDL is still applicable at lower SCRs of the target compared with JDL. [ABSTRACT FROM AUTHOR]

This letter proposes an improved synthetic aperture imaging algorithm to enhance the imaging performance in the Azimuth Missing Data (AMD) case. The proposed algorithm designs an effective phase compensation function based on the Range Cell Migration Correction (RCMC) echo and first reconstructs the complete RCMC echo from the AMD echo. The accuracy of echo reconstruction is improved, leading to a better imaging result. Numerical simulations and a real measured experiment verify the effectiveness of the proposed algorithm. Furthermore, since the range positions of targets can be located after RCMC processing, only non‐zero RCMC signals are reconstructed. Thus, the computational complexity superiority of the proposed algorithm is obvious, especially when the targets are sufficiently sparse in the range direction. [ABSTRACT FROM AUTHOR]

This study introduces a new scheme for resolving the ambiguity in a pulse‐Doppler radar. While ambiguity resolution is typically performed before tracking, the proposed approach, Track‐Before‐Resolving, is resolving ambiguity utilising tracking filters. A specific Doppler ambiguity resolution algorithm is provided for demonstrating that the Track‐Before‐Resolving method is useful. In order to resolve the ambiguity, which is equivalent to finding the ambiguity number, this algorithm investigates the maximum probability calculated in the multiple model estimation, each with a tracking filter of a different ambiguity number. Simulation shows that the proposed algorithm performs effectively, even at low SNR. [ABSTRACT FROM AUTHOR]

This letter formulates a high‐dimensional multi‐objective optimization model to minimize all correlation function values for multiple input multiple output (MIMO) radar waveforms. Then, to solve this problem, this letter proposes an adaptive weighted cyclic algorithm‐new (CAN), named p‐norm weighted cyclic algorithm‐new (p‐WeCAN). Specifically, the adaptive weight updating function is constructed using p‐norm to minimize peak side‐lobe level (PSL) and integrated side‐lobe level (ISL) simultaneously. Numerical results show that the p‐norm weighted cyclic algorithm‐new obtains similar PSL values as the best PSL minimization algorithm and low integrated side‐lobe level values close to its lower bound at the same time. [ABSTRACT FROM AUTHOR]

Due to the technical barriers between radars and jammers and the poor performance of the traditional detection‐jamming shared signal in integrated radar‐electronic warfare systems, a new detection‐jamming shared signal waveform based on the virtual force field algorithm (VFFA) is proposed in this article. First, a multiobjective and multidimensional characteristic parameter optimization model, based on a virtual force field, is established, and then the design principle of the shared signal is presented in detail. The simulation results show that the detection‐jamming shared signal based on the VFFA presents the deceptive jamming of multiple false targets in a noncollaborative target's radar screen. Further, there is better detection performance with the advantages of multiple pulse repetition frequency (PRF) and pulse accumulation numbers, which are highly sensitive to the multijagged PRF signals emitted by the noncollaborative target. According to the VFFA described in this article, the optimum detection‐jamming shared signal waveform can be output in real time for specific free space targets, to improve the efficiency of integrated radar and electronic warfare systems. [ABSTRACT FROM AUTHOR]

Increasingly complex electromagnetic environment makes some troubles for a radar system. Improving the performance of the radar detection and suppressing the interferences are important challenges. In this study, joint transmit filters and sparse array design enabling the maximum signal to interference plus the noise ratio (SINR) beamforming at the transmit subaperturing frequency diverse array multiple‐input multiple‐output (TS‐FDA‐MIMO) radar is examined. However, the optimisation problem is non‐convex. A cycle iteration algorithm is proposed to obtain the optimal transmit filters and sparse array. The total problem is divided into two sub‐problems. The first optimisation sub‐problem is the sparse design and the Successive Convex Approximation (SCA) with two‐dimensional reweighted mixed l1, 2‐norm method is introduced to solve the sub‐problem. In addition, the transmit filters design is the second optimisation problem. The sub‐problem is changed to the semi‐definite relaxation (SDR) problem and the Gaussian random method is utilised to obtain the optimal transmit filters. Through the cycle iteration of the two sub‐problems, the optimal solutions are obtained. Finally, the simulation results verified the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In the complex electromagnetic environment of cities, detection and positioning of slow and small unmanned aerial vehicles (UAVs) have always been a very challenging research topic. Usually, multiple radar observation stations are required to detect and track targets. Moreover, each radar observation station requires strict synchronisation, and the system is complex and costly. In view of this, under the condition of known prior information of urban geography, this study proposes a method to locate UAVs in complex electromagnetic environments, which use multiple virtual mirror synchronous radars constructed by multipaths and created by the complex buildings in urban environments. First, the simulation model is constructed, and the corresponding simulation parameters are given. Then, the algorithm for solving the single‐station radar location is proposed, and the algorithm is verified by the simulation of a ray propagation model. Finally, the proposed algorithm is further verified based on the measured data captured by the radar system in Section 2. The results show that the proposed algorithm based on the single‐station radar is able to locate the UAV in both line‐of‐sight and non‐line‐of‐sight site, and its positioning accuracy is better than 1 m. [ABSTRACT FROM AUTHOR]

In this study, the joint design of discrete phase transmit sequences and receive filters with the low peak sidelobe level and integrated sidelobe level in radar systems is considered. The problem is formulated as a minimisation of the peak (integrated) sidelobe level, forcing a unimodular discrete phase constraint at the design stage. To deal with the resulting non‐convex and in general the NP‐hard optimisation problem, an iterative method based on the alternate optimisation approach is proposed. Each iteration of the proposed method involves a non‐convex min–max problem to be solved. In addition, a sequential rank‐one constraint relaxation framework is proposed to initialise the procedure, each iteration of which requires the solution of a convex problem. Simulation results show that using the proposed framework for jointly finding transmit sequences and receive filters leads to a better peak sidelobe ratio and integrated sidelobe ratio for discrete phase sequences than the optimal mismatched filters design approach. [ABSTRACT FROM AUTHOR]

In this letter, the jamming resource allocation problem of distributed jammers cooperatively jamming netted radar system is investigated. A well‐constructed jamming resource allocation model considering jamming beams, jamming power and other influencing factors is established. Random keys are used in this letter to improve the coding mode of genetic algorithm. Simulation results show that in the case of limited jamming resources, the model and algorithm proposed can achieve effective jamming allocation schemes facing a netted radar with any number of radar nodes. [ABSTRACT FROM AUTHOR]

Direction of arrival (DOA) estimation for signals with large time‐bandwidth products is very important in modern communication and radar systems. Traditional narrowband DOA estimation algorithms are not accurate for such wideband signals. Further complexities arise with non‐stationary signals, for example, high chirp‐rate linear frequency modulated (LFM). These complexities imply that achieving real‐time performance with good DOA estimation accuracy is a challenge. This article uses experimentally acquired data on high chirp‐rate LFM signals to validate a channelised version of MUltiple SIgnal Classification (MUSIC) for DOA estimation. This technique eliminates pre‐processing and incoherently combines spatial pseudospectra from individual frequency channels to obtain a single accurate estimate and has much less computational complexity compared to coherent techniques. LFM signals of up to 500 MHz bandwidth and chirp rates of up to 50 MHz/μs have been used in the investigations and results show accurate DOA estimation at low SNR (0 dB). This technique is suitable for even wider operational bandwidths and low latency implementations. To the best of our knowledge, this is the first time DOA estimation for such high chirp‐rate LFM signals has been validated using real experimental data which is also corroborated with validation using synthetic data. [ABSTRACT FROM AUTHOR]

A frequency diverse array (FDA) multiple‐input multiple‐output (MIMO) radar employs a small frequency increment across transmit elements to produce an angle‐range‐dependent beampattern for target angle and range detection. The joint angle and range estimation problem is a trilinear model. The traditional trilinear alternating least square (TALS) algorithm involves high computational load due to excessive iterations. We propose a fast‐convergence trilinear decomposition (FC‐TD) algorithm to jointly estimate FDA‐MIMO radar target angle and range. We first use a propagator method to obtain coarse angle and range estimates in the data domain. Next, the coarse estimates are used as initialized parameters instead of the traditional TALS algorithm random initialization to reduce iterations and accelerate convergence. Finally, fine angle and range estimates are derived and automatically paired. Compared to the traditional TALS algorithm, the proposed FC‐TD algorithm has lower computational complexity with no estimation performance degradation. Moreover, Cramér‐Rao bounds are presented and simulation results are provided to validate the proposed FC‐TD algorithm effectiveness. [ABSTRACT FROM AUTHOR]

Summary: To lower the side lobe level of MIMO (Multi‐input Multi‐output) radar, a new method, diffenence set and diffderential evolution (DSDE), was proposed. The newly proposed method can arrange the location of the linear MIMO radar antenna arrays by differential set (DS) and optimize the excitation amplitude of each antenna by Differential Evolution (DE). DS is a kind of analysis calculation method, which has faster calculation speed than intelligent optimization methods and has solid optimization ability in thinned antenna array optimization problems. Besides, DE is one of the best stochastic optimization methods which can keep the diversity and avoid premature of the population. Consequently, the proposed DSDE can achieve high performance in the arrangement of arrays and excitation amplitude optimization. Numerical experiments are conducted to test the performance of the proposed algorithm, and the results showed that the analysis optimization method and stochastic optimization method are suitable for solving the problem of pattern synthesis of MIMO radar and keep the diversity with better convergence. [ABSTRACT FROM AUTHOR]

In a distributed coherent aperture radar, the time delay differences and the phase differences among received echoes from each pair of transmitter–receiver should be estimated and then can be compensated to realise coherent processing. Most of the existing algorithms improve the outputs of the matched filtered signals of each transmitter–receiver pair separately. In this study, a structure of equal time delay differences existing in the signal model can be exploited to jointly perform coherence parameter estimation. With this idea, a structure-based joint estimation algorithm is presented to enhance the performance of the coherence parameter estimation. Simulation results verify that this algorithm can have better estimation performance compared with some existing algorithms in the case of low signal-to-noise ratios. Especially, its performance advantage is more significant in the multiple nearfield target scenarios. [ABSTRACT FROM AUTHOR]

This study has been made to improve the detection capacity of radar using phase coded waveforms especially the Golay set sequence while keeping the sidelobe ambiguity function to the possible minimum. This Letter begins with a description of Golay complementary sets construction from a graph and a determination of the parameters on which they depend to be optimised after. Then, the simulated annealing (SA) algorithm has been proposed to deal with low ambiguity problem of the Golay set, due to its simplicity and also to its effectiveness to solve this kind of problem. Simulation results show that the optimisation with SA has impressively improved the sidelobe rejection of Golay set sequences with a gain of up to 20 dB. [ABSTRACT FROM AUTHOR]

A millimetre‐wave cloud radar has limitations for observing heavy rainfall because the short wavelength leads to strong attenuation from raindrops. However, recent studies have attempted to estimate the rain rate using attenuation, which becomes greater as the rain intensity increases. The rain‐rate‐retrieval algorithm is developed in the present paper using the Ka‐band cloud radar (KaCR) installed at the Boseong Global Standard Observatory (BGSO) in the Republic of Korea. First, rain profiles were identified using the threshold of reflectivity (Z) and Doppler velocity (DV) averaged for the analysis of layer that minimized the effects of the receiver saturation and classified as low or high rain‐rate cases using the averaged DV. The reflectivity and rain‐rate (Z‐R) relationship was then derived for low rain‐rate cases that showed insignificant effects for signal attenuation. On the other hand, the attenuation and rain‐rate (A‐R) relationship was derived using high rain‐rate cases that showed the dominant effects of attenuation. The attenuation was calculated using a reflectivity gradient between the upper and lower boundaries of the attenuated layer. Finally, the rain‐rate‐retrieval algorithm was designed using the derived Z‐R and A‐R relationship and then applied back to the KaCR. The estimated rain rate in the KaCR was a similar trend to the observed rain rate in the optical rain gauge (ORG), but slightly underestimated. [ABSTRACT FROM AUTHOR]

In this study, a signal design algorithm for radar–communications system is investigated. An arbitrary pulse length orthogonal frequency-division multiplexing with sufficient cyclic prefix (CP-based OFDM) signal is designed as the radar–communications signal, the communication symbols are embedded by proposing an interval linear phase compression (ILPC) modulation. Firstly, the authors construct the model of CP-based OFDM signal, and analyse the impact of the communication symbols embedding. Then, to decrease the impact caused by the communication symbols embedding, the ILPC modulation is proposed. To guarantee the performances of the CP-based OFDM radar–communications signal, a time/frequency domain iterative filtering and clipping method is used. This algorithm can be used to design a CP-based OFDM signal that has a balanced performance in communications and radar. Finally, numerical results are provided to verify the validity of the proposed algorithm. [ABSTRACT FROM AUTHOR]

In practice, medium pulse repetition frequency (PRF) radar system is widely used as it takes both the advantages of low and high PRF radars. However, range and Doppler ambiguities appear in such a complicated system. Traditional target tracking algorithms first threshold raw measurements and obtain points from different PRF, then perform ambiguity resolutions over them to obtain the unambiguous measurements. It leads to a rather poor performance when target signal-to-noise ratio is low. While multi-frame track-before-detect (MF-TBD) is an advantageous method to track weak targets, but it fails to be applied in multiple PRF radar system directly. In this study, two algorithms based on MF-TBD are proposed. Classical ambiguity resolution (CAR) TBD first resolves ambiguities by means of a robust Chinese Remainder Theorem, where the first detection threshold is below the normal threshold, and then MF-TBD is applied for further tracking. The simulation shows that the proposed method significantly outperforms the CAR detect-before-track algorithm. [ABSTRACT FROM AUTHOR]

The wing-beat frequency is one of the most important behavioural parameters of migratory insects and is widely used to distinguish insect species due to the diversity of wing-beat frequency among different species. Traditional insect radar has been able to achieve automatic extraction of the wing-beat frequency. However, its low-range resolution and fixed threshold detection may cause false alarms and reduce the precision of wing-beat frequency. The authors' Ku-band insect radar system enables high-resolution, full-polarised detection of insects, but has not achieved automatic extraction of wing-beat frequency yet. The authors propose an insect wing-beat frequency automatic extraction algorithm based on a Ku-band insect radar system. The algorithm adopts the constant false alarm rate detector and tracks the association algorithm to get target echo automatically and combines the amplitude spectrum method and the phase spectrum method to achieve wing-beat frequency extraction. The authors carried out the outfield experiment using the radar system and used the collected data to test the proposed algorithm. The experiment results confirm that the algorithm can extract the wing-beat frequency of insects automatically based on the Ku-band insect radar system, which can improve system efficiency. [ABSTRACT FROM AUTHOR]

The waveform optimisation problem in cognitive radar is non-convex and will have sub-optimal solutions when solved by the semi-definite relaxation (SDR) technique. Here, a novel nature-inspired waveform optimisation framework is proposed for range-spread target detection in cognitive radar. First, the waveform optimisation problem is formulated using maximum a posteriori probability and Kalman filtering to estimate the target scattering coefficients. To solve this problem more accurately and efficiently, three nature-inspired algorithms (modified particle swarm optimisation algorithm, Bat Algorithm, and Beetle Antennae Search algorithm), as a nature-inspired waveform optimisation (NIWO) approach is proposed. It is demonstrated through computer simulations that the proposed NIWO approach significantly outperforms the SDR approach, showing a promising tool for waveform optimisation in cognitive radar. [ABSTRACT FROM AUTHOR]

This study deals with a tracking problem for hidden human targets using time-division multiple-input-multiple-output through-wall imaging radar (TWIR). An efficient image-domain tracking algorithm is proposed. Specifically, the authors first utilise back-projection algorithm and the phase coherence factor (PCF) to obtain multi-frame high quality images. Then a tracking algorithm via amplitude-distribution-based particle filter is proposed. Experimental data validates that this algorithm has a commendable effectiveness for hidden target tracking. [ABSTRACT FROM AUTHOR]

This study proposes the concept of an electronic–mechanical dual stable platform for radars with a three-axis stable turntable. Based on an assumption, an electron stable equation of the first order is applied to the beam pointing correction of the radar with three-axis stable turntable based on the equivalence principle. Furthermore, through a comparative analysis of two kinds of algorithms, it is shown that when the instantaneous value of the tracking error in the platform servo-loop of the mechanical platform is smaller than a certain range, assuming the conditions are established, the error method of the electron stable equation of the first order can directly replace the electron stable equation of the second order that is applied to the spatial orientation correction of the radar beam to improve computational efficiency. At the same time, error analysis was performed on the data link of the dual stable platform. [ABSTRACT FROM AUTHOR]

In order to solve the problems of slow imaging speed and poor reconstruction accuracy of wall parameters under the condition of wall parameter fuzziness, an improved limited Broyden-Fletcher-Goldfarb-Shanno-particle swarm optimisation (LBFGS-PSO) algorithm was proposed. The LBFGS-PSO algorithm model solves the problems of slow calculation speed and large errors of the traditional quasi-Newton algorithm and particle swarm algorithm. The algorithm combined with block orthogonal matching pursuit algorithm can not only accurately reconstruct the position of the sidewall, but also can use the multi-path information to accurately reconstruct the moving target and the stationary target. Compared with the traditional BFGS algorithm and PSO algorithm, the proposed algorithm can reduce the calculation time and provide more accurate estimation results. Simulation results and data analysis verify the performance of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Based on the purpose of proactive anti-reconnaissance, the essential characteristics of several typical pulse repetition interval (PRI) sorting algorithms were analysed and the feasibility of counter-deinterleaving was discussed. A method for disturbing arrival time sequence by using interference pulse was proposed, which changes the statistical properties of the radar PRI to disturb the deinterleaving results. The simulation results show that the pulse jamming method proposed in this paper can influence PRI sorting process effectively, which let signal processer make a misjudgment on PRI pattern of radar. [ABSTRACT FROM AUTHOR]

Integrated radar and communication system can significantly enhance the work efficiency and considerably occupy less hardware resources. However, the integrated systems have limited supply resources, where a proper scheduling scheme is needed to meet the requirement of systems. Here, the authors propose a task-scheduling scheme based on the greedy algorithm, where each arrangement is the result of selecting the minimum shift time compared with the expected time. By guaranteeing the best result of each task, the minimum average time shift ratio (ATSR) of the whole tasks is obtained. Simulation results show that when the number of the tasks is quite large, the proposed scheme has more advantages than the traditional scheme based on time pointer algorithm. Authors' proposed scheme can significantly reduce the average offset time of tasks while maintaining a satisfactory successful scheduling rate (SSR), which shows more advantages in the integrated systems. [ABSTRACT FROM AUTHOR]

Distributed digital array radar (DDAR) can operate in multiple modes and perform multiple functions. Compared with traditional phased array radars, the performance advantages of DDAR are obvious in many aspects. One of them is that DDAR can form space mesh in a wide scope. This article proposes a new fast mesh forming method. Unlike traditional multiple beam forming, the authors' algorithm can form a mesh along range and azimuth. First, the range profile is obtained based on fast Fourier transform. Second, the mesh forming is divided into several steps that are accomplished in polar formatted plane. Finally, the polar formatted result is transformed into Cartesian coordinates. The authors tested the method using RADBASE data, which shows that the authors' algorithm has good performance. [ABSTRACT FROM AUTHOR]

When there is sidelobe interference in the array pattern, adaptive monopulse angle measurement can suppress interference and improve the accuracy of angle measurement. However, when the interference occurs in the mainlobe, the angle measurement performance will be seriously deteriorated. This problem can be solved well with the monopulse angle measurement algorithm based on auxiliary array. Here, auxiliary array radars are added to the main radar to extend the aperture of the array, and using the MSINR criterion or MMSE criterion to suppress the mainlobe interference, a good measurement accuracy can be obtained. The effectiveness of the method is proved by computer simulation. [ABSTRACT FROM AUTHOR]

Through-the-wall radar has been used in rescue missions, behind-the-wall targets detection, surveillance and reconnaissance etc. However, through-the-wall radar encounters two major problems in complex environment. One is that the refraction of the unknown wall would distort the through-the-wall image. The other is that the multi-reflection between wall and walls as well as wall and targets would lead to a lot of fake targets. To solve these problems, a multi-path suppression algorithm is proposed in this study. The simulation results show that proposed algorithm can automatically estimate the thickness and dielectric parameter of the unknown wall and give an undistort image, and remove the fake targets due to the multi-path effect. [ABSTRACT FROM AUTHOR]

An iterative adaptive approach (IAA) based algorithm is presented to realise coherent integration for the random pulse repetition interval radar. The proposed method firstly removes the effect of Doppler ambiguity via phase compensation, and then accomplishes target focusing via conducting the azimuth IAA and range inverse fast Fourier transform. Theoretical analysis and numerical experiments have verified the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

By using the operation of two VHF radars of the Voronezh and Resonance class of the Russian Federation as an example, an analysis of the main directions of radiowaves propagation characteristics influence on the operation of such radars and improving the algorithms for correcting this influence was made. [ABSTRACT FROM AUTHOR]

This study proposes a new algorithm for air target radar imaging by taking the geometrical and processing advantages of array antenna systems. The backscattered signal is processed with a new technique to benefit the facilities of angular scanning. In order to virtually increase the number of the radar elements of the array system, a powerful optimal estimator is employed, namely Kalman filter. [ABSTRACT FROM AUTHOR]

There exist few rapid reconstruction methods for applications that use multistatic radar for targets in the near field such as vehicle navigation and personnel screening. Fourier accelerated multistatic imaging (FAMI) is a method that combines the rapid reconstruction speed of Fourier-based imaging algorithms with the flexibility of algebraic algorithms that allow arbitrary radiation patterns and antenna placement. Many of these new applications image in the near field of the individual antennas of a multistatic array, however, FAMI contains approximations that require the target to be in the far field of each antenna. Stretchedphase FAMI (SP-FAMI) overcomes this limitation and allows imaging in the Fresnel region of the antennas so that targets may be very close to the array while retaining the computational benefits of Fourier reconstruction. As radar wavelengths decrease with a corresponding increase in resolution, SP-FAMI allows the imaging of nearby targets that would otherwise be too close for FAMI to image accurately. [ABSTRACT FROM AUTHOR]

The intra-pulse phase change caused by frequency difference of arrival (FDOA) is very little and even omitted due to extremely short duration of emitter pulses that the joint location using time difference of arrival (TDOA) and FDOA cannot be realised. To solve this problem, a multi-pulse coherent accumulation algorithm of direct position determination (DPD) using the TDOA and FDOA is proposed in this study. Through establishing coherent signal model of short pulses which is deterministic but unknown, the maximum likelihood estimator for localisation of a stationary emitter using multiple moving receivers is derived by taking the DPD approach under additive Gaussian white noise environment. This study also derives a signal-specific Cramer--Rao lower bound (CRLB) of DPD, modelling the signal as a deterministic unknown. The CRLB is more applicable to some specific (non-stationary, non-Gaussian) signals, especially electromagnetic signals. Simulation results show that the proposed method achieves a significant performance improvement in locating accuracy over the existing methods and its accuracy is close to the CRLB in normal signal-to-noise ratio. [ABSTRACT FROM AUTHOR]

This study deals with the problem of adaptive radar detection when a limited number of training data, due to environmental heterogeneity, is present. Suppose that some a priori spectral models for the interference in the cell under test and a lower bound on the power spectral density (PSD) of the white disturbance term are available. Hence, generalised likelihood ratio test-based detection algorithms have been devised. At the design stage, the basic idea is to model the actual interference inverse covariance as a combination of the available a priori models and to account for the available lower bound on the PSD. At the analysis stage, the capabilities of the new techniques have been shown to detect targets when few training data are available as well as their superiority with respect to conventional adaptive techniques based on the sample covariance matrix. [ABSTRACT FROM AUTHOR]

Power allocation in distributed multiple-input multiple-output radar is investigated for range-only target localisation such that the determinant of Bayesian Fisher information matrix (B-FIM) is maximised. The B-FIM is derived from a signal model that incorporates the propagation path loss, the target reflectivity, the transmitted power and target prior information. The authors model the problem as a cooperative game and exploit the solution concept of Shapley value to distribute a given power budget among all transmitting radars for localisation and integrate the algorithm with a sequential Bayesian estimator to localise target. In numerical simulations, it is shown that uniform power allocation is not in general optimal. They illustrate the impact of the radar antenna geometry and target location prior density on the allocation results and demonstrate the superior performance of the proposed optimal power allocation scheme via Monte Carlo simulations. [ABSTRACT FROM AUTHOR]

A set of quality control algorithms developed in the framework of the RADVOL-QC system is described. The algorithms are dedicated to 3-D radar reflectivity data (volumes) provided by a weather radar with single-polarization of the beam. The system consists of two paths of data processing: quality correction and quality characterization. Processing by means of data correction algorithms allows the reduction of uncertainty in the data, whereas quality characterization algorithms generate a map of quality index (QI) that can be attached to the data. The following correction algorithms are included in the proposed scheme: (1) removal of geometrically shaped non-meteorological echoes (from the Sun and other emitters); (2) removal of measurement noise (specks); (3) beam blockage correction, and, (4) attenuation in the rain correction. The list of quality characterization algorithms is longer, as it also includes evaluation of data uncertainty due to technical radar parameters, distance to radar related effects, and ground clutter. All the algorithms have been developed paying special attention to possibility of operational application. The system is planned to be extended successively by other quality factors. Copyright © 2012 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

This paper proposes an acceleration technique to fast evaluate the monostatic radar cross section (RCS) with the multilevel physical optics (MLPO) algorithm. The proposed method combines the adaptive cross approximation (ACA) algorithm with the MLPO to fast evaluate two-dimensional monostatic RCS (two-dimensional monostatic RCS over a range of elevation angles φ and azimuths angles j at a fixed frequency f, or a range of frequencies f and azimuths angles φ at a fixed elevation angle θ) responses. Owing to the phase compensation in the MLPO, the matrix corresponding to the compensated back-scattered field of each group is highly rank-deficient, which is compressed with ACA in a multilevel fashion therefore a lot of central processing unit time will be saved. The rank-deficiency, accuracy and computational complexity of the proposed method have been studied through a couple of numerical examples, which illustrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

The study aimed to analyze the spatial variability of surface soil moisture at different spatial scales based on field measurements and remote sensing estimates. Multitemporal Envisat satellite Advanced Synthetic Aperture Radar (ASAR) data were used to derive the surface soil moisture utilizing an empirical C-band retrieval algorithm. Eight wide-swath (WS) images with a spatial resolution of 150 m acquired between February and October 2008 were used to determine the surface soil moisture contents. The accuracy of the surface soil moisture retrievals was evaluated by comparison with in situ measurements. This comparison yielded a root mean square error of 5% (v/v). Based on our in situ measurements as well as remote sensing results, the relationship of the coefficient of variation of the spatial soil moisture patterns and the mean soil moisture was analyzed at different spatial scales ranging from the catchment scale to the field scale. Our results show that the coefficient of variation decreases at all scales with increasing soil moisture. The gain of this relationship decreases with scale, however, indicating that at a given soil moisture state, the spatial variation at the large scale of whole catchments is larger than at the field scale. Knowledge of the spatial variability of the surface soil moisture is important to better understand energy exchange processes and water fluxes at the land surface as well as their scaling properties. [ABSTRACT FROM AUTHOR]

The article focuses on study of the development of infrared-microwave rainfall algorithm (IMRA) to retrieve spatial rainfall from infrared (IR) brightness temperatures (TBs) of satellite sensors. IMRA was made to discriminate rain/no-rain pixels through IR image cloud-top temperature gradient. The result of the study indicates that the SLOPE technique (ST) option of IMRA gave precise satellite rainfall estimate for both light and heavy rainfall systems.

A sparse approximate inverse (SAI) preconditioning of deflated block-generalized minimal residual (GMRES) algorithm is proposed to solve large dense linear systems with multiple right-hand sides arising from monostatic radar cross section (RCS) calculations. The multilevel fast multipole method (MLFMM) is used to accelerate the matrix–vector product operations, and the SAI preconditioning technique is employed to speed up the convergence rate of block-GMRES (BGMRES) iterations. The main purpose of this study is to show that the convergence rate of the SAI preconditioned BGMRES method can be significantly improved by deflating a few smallest eigenvalues. Numerical experiments indicate that the combined effect of the SAI preconditioning technique that clusters most of eigenvalues to one, coupled with the deflation technique that shifts the rest of the smallest eigenvalues in the spectrum, can be very beneficial in the MLFMM, thus reducing the overall simulation time substantially. Copyright © 2008 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Besides air, the millimeter wave (MMW) provides another valuable medium to conduct speech, which may extend the traditional speech detecting method, and provides some exciting possibility for wide applications. However, the MMW conduct speech is in less intelligible and poor audibility since it is corrupted by additive combined noise. This article, therefore, proposed a simple and efficient way to take into account properties of the auditory system in the enhancement processes. The parameters of the spectral subtraction algorithm can be adaptive adjust in a perceptual sense based on a tradeoff between amount of noise reduction, the speech distortion, and the level of musical residual noise. The results from both simulation and listening evaluation suggest that the background noise can be reduced efficiently while the distortion of MMW radar speech remains acceptable, the enhanced speech also sounds more pleasant to human listeners, resulting in improved results over classical subtractive-type algorithms. © 2008 Wiley Periodicals, Inc. Microwave Opt Technol Lett 50: 2109–2114, 2008; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.23588 [ABSTRACT FROM AUTHOR]

This article presents efficient technique of two-dimensional (2D) scattering center extraction and inverse synthetic aperture radar (ISAR) image formation of a target. The proposed technique uses a sparse scanning order conception and modified spatial smoothing preprocessing (MSSP). The MSSP is used to construct autocorrelation matrix. In general, 2D IFFT (inverse fast Fourier transform) is widely used to obtain 2D scattering center and ISAR image. This method is computationally efficient, but has drawbacks that are poor in terms of resolution. To overcome these shortcomings with the IFFT-based method, various high-resolution techniques were developed. The proposed algorithm enables us to provide exact scattering centers and ISAR image of a target. In order to show the performances of the proposed technique, we use backscattered field data of the ideal point scatterers and the F-18 aircraft to estimate 2D scattering centers and obtain 2D ISAR image. © 2008 Wiley Periodicals, Inc. Microwave Opt Technol Lett 50: 2173–2178, 2008; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.23619 [ABSTRACT FROM AUTHOR]

In this paper, the capability of the integer ambiguity method to find the absolute position of InSAR data is demonstrated. A radargrammetric model is used for the space triangulation. The method is demonstrated using ERS data of the Thames region and the results are compared to GPS measurements and a digital elevation model. The GPS stations, not visible in the image, are located on the InSAR data using a simple range-Doppler algorithm and an analysis of their positions is undertaken. The results are consistent with other methods but with the advantage that the radargrammetric model is very simple. The results also highlight the problems of integrating GPS data with InSAR data in urban areas where a GPS station may not be representative of the dominant scatterers within a resolution cell, and they suggest methods that might be applied in future to reduce this problem. The model should help the integration of InSAR data with other geometric survey data. [ABSTRACT FROM AUTHOR]

In order to calculate 3D electromagnetic scattering problems by dielectric objects which we need to solve a large-size simultaneous linear equation, we present a rapid algorithm on the Yasuura method where we accelerate the convergence rate of solution by using an array of multipoles as well as a conventional multipole. As a result, we can obtain the radar cross sections of dielectric objects in the optical wave region over a relatively wide frequency range and a TDG pulse response. Furtherrmore, we analyze the scattering data about dielectric objects by using the pulse responses cut by an appropriate window function in the time domain and clarify the scattering processes on dielectric objects. © 2004 Wiley Periodicals, Inc. Electr Eng Jpn, 148(2): 39–45, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ eej.10292 [ABSTRACT FROM AUTHOR]

Multiple-beam antenna arrays have important applications in communications and radar. This paper describes a method of designing a reconfigurable dual-beam antenna array using a new evolutionary algorithm called particle swarm optimization (PSO). The design problem is to find element excitations that will result in a sector pattern main beam with low side lobes with the additional requirement that the same excitation amplitudes applied to the array with zero phase should result in a high directivity, low side lobe, and pencil-shaped main beam. Two approaches to the optimization are detailed. First, the PSO is used to optimize the coefficients of the Woodward–Lawson array synthesis method. Second, the element excitations will be optimized directly using PSO. The performance of the two methods is compared and the viability of the resulting designs are discussed in terms of sensitivity to errors in the excitation. Additionally, a parallel version of the particle swarm code developed for a multi-node Beowulf cluster and the benefits that multi-node computing bring to global optimization will be discussed. © 2003 Wiley Periodicals, Inc. Microwave Opt Technol Lett 38: 168–175, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.11005 [ABSTRACT FROM AUTHOR]