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In order to obtain clearer interference pattern of interferometric radar and obtain more accurate detection target, this paper studies the influence of atmospheric turbulence on axial transmission beam. The response of random wave number and transmission distance to amplitude fluctuation and phase fluctuation is discussed respectively. The aim is to establish a phase compensation plate in the reference optical path, so that the interference optical path and phase can meet a specific range, and to promote the development of interferometric radar technology. The study shows that the random wave number caused by atmospheric turbulence has obvious influence on amplitude fluctuation and phase fluctuation, and transmission distance is relatively weak influence on them. As the change of random wave number and transmission distance, the amplitude fluctuation and phase fluctuation will also change. The phase compensation plate should be selected integrated according to the atmospheric turbulence intensity and transmission distance.

Accuracy and speed of parameters estimation for radar signal is very important in optical wireless communications. In order to implement high accuracy and fast speed of parameters estimation, a new estimation algorithm is presented in the paper. The method is based on quadratic phase function (QPF) and fractional Fourier transform (FRFT), which is used to estimate parameters for the chirp signal. In order to avoid two-dimensional searching during FRFT, chirp rate is directly estimated by QPF method, and then the optimum transform order of FRFT is calculated by estimating the chirp rate. Finally, center frequency and amplitude of the chirp signal are estimated by FRFT. Simulation results show that the proposed QPF-FRFT method is faster than the FRFT method and two step maximum modulus searching method. Otherwise, when the SNR is higher than -4dB, the center frequency, chirp rate and amplitude of chirp signal can be estimated by QPF-FRFT method more accurately than FRFT method. In conclusion, results on experimental of chirp signal illustrate the efficient performance of the algorithm.

A photonic approach to wideband Doppler frequency shift (DFS) measurement and direction discrimination is proposed and demonstrated. In the proposed scheme, a dual-parallel Mach-Zehnder modulator is used to generate carrier suppressed double sidebands signals, which are orthogonally polarized in a Sagnac loop incorporating a fiber Bragg grating. The DFS is transformed into a low-frequency electrical signal. The value of the DFS is obtained by analyzing the spectrum of the output current. The orientation of the DFS is estimated by a 90° hybrid coupler. The entire DFS measuring process is independent of the radar carrier frequency and suitable for wideband spectrum measurement range. Simulations are performed to verify the proposed scheme, the value and the orientation of the DFS can be estimated simultaneously. As the target moves toward the radar or moves away from the radar, there are, respectively, 36.8 dB and 39.1 dB power difference between the two branches of the hybrid coupler. In addition, the performance of the proposed approach in term of the signal-to-noise ratio and stability are discussed.

Classification of ground vehicles from the unmanned aerial vehicles (UAVs) is the basis for local precision strikes. In this paper, a method based on micro-Doppler effect which provides unique information of targets is proposed for ground vehicles classification. Firstly, models describing the air-to-ground relationship between ground vehicles and the UAV are built to derive mathematical expressions of radar echo signals. Secondly, Singular Value Decomposition (SVD) is utilized to analyze micro-Doppler components of the ground wheeled vehicle and the ground tracked vehicle respectively. Thirdly, according to classify requirements, specific signal components are restored by Singular Value Reconstruction (SVR). Seven micro-Doppler features are extracted from reconstructed signals. At last, these features are sent to Support Vector Machine (SVM) classifier. Compared with current related methods such as Empirical Mode Decomposition (EMD) and multi-level wavelet decomposition (MWD), experimental results in different cases illustrate the effectiveness of this method. Discrimination performance under various signal-to-noise ratios (SNRs) also proves the robustness of proposed method.

A robust cardinalized probability hypothesis density based on interacting multiple model (RCPHD-IMM) is proposed for multiple maneuvering targets tracking under the Doppler blind zone of airborne pulse Doppler radar. This tracking algorithm integrates the advantages of unbiased converted measurements (UCM), interacting multiple model (IMM), and cardinalized probability hypothesis density (CPHD). Under the architecture of the proposed algorithm, an IMM deals with the model switching, and the UCM accounts for nonlinearity in the dynamic system models, whereas the CPHD estimates the number and state of the targets. The gain adjustment matrix is designed to improve the robustness of the proposed algorithm in the blind zone. Furthermore, an adaptive gating strategy is proposed to remove the irrelevant measurements and guarantee the detection of new targets, thereby effectively reduce the computational complexity of the proposed algorithm. Simulation results demonstrate the validity and feasibility of the proposed algorithm. The number and state of the targets in the loss of measurements can be estimated more accurately, and the amount of calculation needed with the RCPHD-IMM algorithm is reduced by 16.03% compared with the traditional CPHD algorithm.

Haze and rain are the most impairments factors to free space optical (FSO) links. These weather conditions limit the visibility, and thereby causes high attenuation of the optical signal. This high attenuation reduces the availability performance of the FSO link. This study evaluates the performance of a terrestrial FSO link under tropical climate conditions. The performance analysis is evaluate over 5 km link distance. The cumulative distribution function (CDF) of the received signal to noise ratio (SNR) is used to study the outage performance of the FSO link under haze conditions. The performance analysis is based on three years measured visibility data in Malaysia. Based on the statistical analysis, link availability of 99.99% can be achieved for 37.44 dB SNR over 1 km link distance. Carrier class availability “five nine” can be achieved for 20 dBm transmission power using 1550 nm wavelength.

Loop-closure detection plays an important role in visual simultaneous localisation and mapping;it is an independent part of the visual odometer and can effectively reduce its accumulated error, in addition to helping with loop-closure detection for relocalisation. With the development of deep learning methods in recent years, the training models of convolutional neural networks for major data sets have been improved for loop-closure detection. Presently, some high-level engineering problems still rely on auxiliary equipment, such as panoramic cameras and radar lasers, which greatly increase the expensive extra cost; however, owing to the extreme appearance and viewpoint changes involved in such problems, loop-closure detection that relies on two-dimensional images is not applicable. Based on the two nearest neighbour vector of locally aggregated descriptors (TNNVLAD) method, a novel feature descriptor called two nearest neighbour local sensor tensor(TNNLoST) is proposed herein by combining the semantic features of high-level neural networks with dense descriptors. This approach introduces a semantic concept similar to human cognition for the surrounding environment, thus enabling better understanding of the environment. The proposed method was applied to publicly available benchmark datasets to show its performance.

Characteristics of Radar Cross Sections (RCS) in the presence of ferrite coating layer on perfect electromagnetic conductor sphere have been studied theoretically and analytically. Spherical wave vector functions were used to expand the incident, scattered and transmitted electromagnetic field components. Co and Cross polarized scattered field components have been evaluated by applying PEMC boundary conditions at both interfaces, i.e., free space- ferrite layer and at ferrite layer-PEMC sphere core. By using obtained values of the Co and Cross polarized scattering coefficients, the forward and backscattered Radar Cross Section were calculated and compared with already published literature. The effects of applied dc bias magnetic field, saturation magnetization, incident frequency, sphere radius and relative permittivity on forward and backscattered radar cross section were analyzed in graphical form.

Driving environment perception technology is a key issue for driving assistance systems and autonomous vehicles. Driving environment information collection and information fusion and representation are two important contents of this technology. On-board sensors such as camera, radar, lidar, etc., are popularly used to collect relevant information. However, when using these on-board sensors, uncertainty arises from ignorance and errors, where ignorance is usually caused by vehicle occlusion, and errors is caused by imprecise pose estimation and noisy measurements. Increasing sensor number would decrease such uncertainty, but complexity and cost is also increased in this way. In this paper, we present a V2I (vehicle-infrastructure) based urban driving environment collection method achieved only by two sensors, i.e., a Road Side Unit camera (RSU camera) and vehicle GPS. RSU camera is used to extract lane marking information, including position and type, and vehicle position information. Vehicle GPS provide position information of vehicle. A credibility map is proposed as the compact representation of urban environment, and accept those information from RSU camera and vehicle GPS. In order to hand uncertainty caused by sensors, Dempster-Shafer theory is employed to estimate the credibility of each cell, fuse the credibility root in the information provided by RSU camera and vehicle GPS, and map onto the credibility map. The performance of this method has been validated with real-world urban traffic data.

This paper proposed a blind spot detection and warning system named BSDW for driver assistance under daytime and nighttime conditions. The proposed BSDW system includes system architecture platform, radar hardware system structure, intermediate frequency signal processing, radar target detection algorithms, blind spot area calibration method, system control strategy and system integration. Line frequency modulated continuous wave millimeter-wave radar was used to detect moving targets which come into the rear blind spot alarm area, including left, right and behind area of the subject vehicle. Based on Rayleigh clutter distribution model, a cell greatest, smallest and averaging constant false-alarm rate target detection algorithm named CGSA-CFAR was proposed to maintain higher detection rate and lower false-alarm rate by adjusting power detection threshold in time based on the noise power level, which was estimated according to the proposed target detection algorithm. The proposed system was implemented on embedded hardware platform and verified on the Chery Arrizo7 vehicle. Under urban daytime and nighttime conditions, the early warning rates of the proposed system were up to 98.20% and 98.21% respectively. The results show that the proposed system can detect the targets which come into the rear warning area of the subject vehicle and give early alarm to driver effectively in various urban road environments.

Availability is one of the major parameters to measure the performance of Free Space Optics (FSO) communication link. In tropical climate, rainfall acts as a dominant factor that affects the FSO link availability; whereas haze has no significant effect compare with rain. But for longer FSO link distances, the effect of haze on the overall FSO link availability becomes serious and need to be considered. In this paper, availability of an FSO link is estimated under the impact of rain, haze and the combination of the two phenomena. The availability estimations based on predicted attenuation due to rain and haze using long-term statistical measurements of rain rate (mm/hr) and visibility (km) data measured in Malaysia. The effect of individual weather phenomena was demonstrated over FSO link ranges from 1 to 5 km. The combine effect of both rain and haze also has been analyzed using the cumulative distribution function (CDF) of predicted atmospheric attenuations. In tropical regions, for short FSO link distance, the influence of haze on the availability of FSO signal is negligible compare with rain; whereas for longer FSO distances, haze attenuation will reduce the overall link availability. This effect of haze needs careful consideration for the deployment of FSO systems especially in Malaysian tropical climates.

In this paper, a radar cancelling stealth system for linear frequency modulated signal is proposed. This system is based on interrupted-sampling and convolution modulation. The basic theory of active cancellation stealth is introduced. Based on three conditions that should be met for radar echo cancellation, the restrictions for three key parameters are deduced in theory. The influence of amplitude, phase and frequency error have been discussed. And the cancelling scheme and working principle are also introduced in detail. Finally, numerical simulation results show that the active cancelling approach is feasible and effective.

Using radar to detect multiple high-speed targets is a process that can be equivalently expressed by detection of multiple linear frequency modulation signals. In this paper, preliminary detection is performed on multiple signals using short-time Fourier transformation (STFT) and then the preliminary detection results are treated using binaryzation, during which the phase information of the signals are preserved. Then, detection is made using fractional Fourier transformation. The combination of the two techniques is advantageous because the phenomena of strong signal side lobe suppressing weak signal main lobe is avoided and the signal-noise ratio (SNR) of the to-be-detected signals is improved. Meanwhile, image contrast and successive elimination are introduced in target isolation process, which helps increase the utilization of signals in space and frequency dimensions, with the result that the detection probability of target signals are further enhanced.

This paper mainly studies the application of the fractal self-affine theory for weak target detection in sea clutter. In this paper, the adaptive 3D-IFS (3D-IFS: three-dimensional iterated function system) algorithm is presented and a novel weak target detection model is proposed based on the algorithm. To accurately extract the weak target from the complicated background of sea clutter, we use the radar echo model of the LFM radar and the target detection model to calculate the prediction error of radar echoes. Furthermore, based on extensive analysis and simulation, we identify the scale factor, polarization model and target state as three key factors that affect the detection performance of our proposed model. Using the real data from IPIX radar and C-band radar for simulations, we can see that the model has a significant performance improvement for weak target detection compared to the traditional 3D-IFS algorithm. The detection probability of the model reaches 70% at the SCR near −10 dB, and signal processing time of the model is approximately 0.3 s at the SCR near −6 dB, thus it meets the requirement for low-observable ( SCR > −8 dB) and radial velocity about 600 m/s high speed weak target detection in sea clutter.

Frequency modulation (FM) signal is widely used in the sonar, radar, laser and newly developed optics cross-research fields, its compactness (or sparsity) plays an important role in the FM signal sampling, reconstruction, compression and denoising. This paper is devoted to studying the compactness of FM signal, a minimum l p - norm method (MPNM) is proposed to estimate the compactness of FM signal in the fractional Fourier transform (FRFT) domain. Compared with the existing methods, the compact FRFT domain of FM signal obtained by this method has better sparsity. Furthermore, the proposed method is successfully applied to the denoising of linear FM signal.

The sequential phase rotation (SPR) technique has been used to enhance the impedance and axial ratio bandwidths of the CP array antennas. In this paper, a broad band CP antenna array for X-band applications using SPR technique is designed and analyzed. The designed antenna is capable of operating between 8.93 GHz–12.82 GHz while the S11 is less than -10 dB and exhibits CP operation between 9.23 GHz and 12.47 GHz with an axial ratio less than 3 dB. The array attains the maximum peak gain of 9.88 dB. The CP array can produce good circular polarization over the broad band frequencies by utilizing the square patch with truncated corners as the basic element of the array and providing the suitable amount of sequential phase among the elements. This array may find widespread applications in radar and satellite communications. The array antenna was fabricated and tested. There is a good agreement between simulated and measured results.

In this paper, precision model, rough model and accurate model with YF-23 as original reference are established. The precision model is obtained by fine modeling based on pictures; the rough model is obtained by rough modeling based on pictures; the accurate model is obtained by fine modeling based on point cloud model. Three models correspond to three modeling methods in engineering practice. Based on the multilevel fast multipole algorithm (MLFMA), the vertical polarization transmitting/vertical polarization receiving (VV) and horizontal polarization transmitting/horizontal polarization receiving (HH) radar cross section (RCS) characteristics of three models were simulated at low and high frequencies. The relationship between aircraft surface details and radar stealth performance were investigated and analyzed according to the simulation results.

To improve the radar scattering characteristics of the target in the head direction, a narrow surface element (NSE) method based on physical optics (PO) and physical theory of diffraction (PTD) is presented. When solving the radar cross section (RCS) of the surface to be optimized, the surface needs to be decomposed into a number of narrow surfaces, each of which has a single column of interlaced triangular face element. Within a given range of variation, the mesh information of the surface could be determined by the NSE method to obtain the required RCS distribution. Taking an asymmetric surface as an example, the NSE method is used to determine the minimum RCS of the surface, thereby improving the head-to-stealth performance of the target. The proposed NSE method is effective and efficient for the fast optimization of the surface RCS.

Radar absorbing materials (RAMs) have been widely applied in the fields of electromagnetic shielding and target camouflage. The current radar absorbing materials are passive, and the frequency response and absorption features are fixed as soon as they are prepared, which limits their further application in the future. In this work, a sort of state-of-the-art broadband tunable radar absorber is designed, fabricated and measured. The active metamaterial absorber and passive absorbing honeycomb are creatively combined together to achieve the overall absorptance of less than -10 dB in frequency range of 7˜22 GHz. Furthermore, PIN diodes are introduced into the metamaterial radar absorber. By adjusting the bias voltage of the PIN diode array, the radar absorbing property can be actively tuned in a wide frequency range in the condition of broadband and high efficiency absorption.

This paper presents an active stealth system for the linear frequency modulation (LFM) signal which based on the group delay of it. The cancelling system structure is given and the conditions that can be generated for cancelling the radar echo are presented. By making the LFM signal and its delayed signal multiplication to obtained the frequency difference between them. And then frequency shift the LFM signal using the difference. Finally, according to the target's RCS database by amplitude and phase modulation to get the cancelling signal which having the same frequency as the echo pulse but with the opposite phase. Theoretical analysis and simulation show that the system can workable when the phase error and the time delay is relatively large.

Ground-penetrating radar was simulated using the FDTD method with uniaxial anisotropic perfectly matched layers as absorbing boundary conditions. To study underground pipeline detection, the electromagnetic response properties of underground pipelines, under known soil conditions, were determined. Pipelines at different depths and with different diameters and different compositions were simulated and researched for their response. The simulation results were consistent with research and analysis, i.e., the deviation was in an acceptable range. This research is of great value to guide the detection of pipelines in cities and to explain the detection of materials underground.

In radar systems, the echo signal caused by an accelerated target can be similarly considered as linear frequency modulation (LFM) signal. In high signal-to-noise ratio (SNR), discrete polynomial-phase transform (DPT) algorithm can be used to detect the echo signal, as it has low computation complexity and high real-time performance. However, in low SNR, the DPT algorithm has a large mean square error of the rate of frequency modulation and a low detection probability. In order to detect LFM signal in low SNR, this paper proposes a detection method, segment discrete polynomial-phase transform (SDPT), which means, at first, dividing the whole echo pulses into several segments with same duration in time domain, and then, using coherent accumulation method of DFT to segments, at last, processing this signal with DPT in intra-segment. In the case of a large number of segments, the SDPT can improve the output SNR. In addition, in a certain SNR, to the target signal with big sampling interval, large acceleration and less segments, this paper proposes an algorithm to detect the LFM signal generated from the combination of an improved DPT (IDPT) and fractional Fourier transform (FRFT). The output SNR of this algorithm is connected with the length of time delay. In the simulation, when the length of the time delay is 0.2 N, the output SNR is 2.5 dB more than that which results from directly using DPT. Finally, the detection performance and algorithm complexity of the proposed algorithm were analyzed, and the simulated and measured data verify the effectiveness of the algorithm.

Micro-Doppler effect is induced by the micro-motion dynamics of the radar target itself or any structure on the target. Spinning, coning and wobble are typical basic micro-motions of missile warhead. In this paper, a cone-shaped model for missile warhead with micro-nutation is established under the case of bistatic radar system, followed by the theoretical formula of bistatic micro-nutation is derived. Using the method of short-time Fourier transform, which confirms the simulated results are identical to the theoretical results. In addition, in order to further approach the actual environment. Base on micro-Doppler effect, the effective scattering center model with occlusion effect is considered under the case of bistatic radar system. The simulated results are compared with the fixed scattering point model without the occlusion effect. By the simulation studies, it shows the otherness between the actual environment and ideal assumption. A certain of theoretical analysis conclusions for extracting the features of missile warhead in bistatic radar system are gained, which can be applied to radar target recognition in the future work.

Active cancellation stealth is a smart signal blanking method, that it has become an important developing direction on modern stealth technology. In order to further explore the active cancellation stealth technology, we are considering the detection and cancellation of receiving/transmitting antenna pattern is different. Put forward active cancellation system simulation structure diagram based on MATLAB/SIMULINK, where the phased array radar system as the modelling object, and established the active cancellation stealth system mathematical model based on digital radio frequency memory (DRFM) and the radar signal processing system of the coherent video simulation model, based on linear frequency modulation and radar coherent pulse signal simulation, verified the rationality and validity of the design, as the active cancellation stealth engineering technology laid the foundation.

A detection method of the weak radar target is studied by applying fuzzy theory and multifractal correlation theory based on a two-dimensional fractal sea surface model. Firstly, a two-dimensional fractal sea surface model and its backscattering coefficient are introduced, the backscattering coefficient is a universal model affected by seawater permittivity, electromagnetic wave incidence angle, incident frequency, wind speed and wind direction factors. A novel two-dimensional wideband radar echo model, which is considered as a time-domain convolution of the stepped frequency signal radiated by airborne radar and the backscattering coefficient, is derived. Secondly, multifractal correlation theory is elaborated and a computation method of a membership degree of multifractal correlation spectrum is proposed, fuzzy theory and the AdaBoost algorithm are applied to the target detection. Finally, several target detection methods are compared with CA-CFAR and works of the predecessors. The results of the comparative study show its rationality of the two-dimensional wideband radar echo model and the superiority of wideband radars in detection performance, it is also seen that the multifractal correlation spectrum outperforms the multifractal spectrum in the probability of detection.

An integrated microwave photonic phase shifter based on vector-sum technique in silicon on insulator was verified and designed. The principle of phase-shift was demonstrated and the components were designed in detail. The interference was taken into account in the design and 0.3 nm line-width of a light source was required to make the coherent interference smallest even to be neglected. Owing to the compact size and excellent characteristics of integration, the proposed component has a promising utilization in optical communication and optical phased-array radar.

A cancelling system for the four nonlinear frequency modulated (NLFM) signal (i.e. Taylor window, Tangent-based, Combination linear frequency modulation (LFM) and tan-FM, Stepped NLFM) is presented. It is mainly composed of a digital radio frequency memory (DRFM) and a field programmable gate array (FPGA) chip etc. The received signals are stored and reproduced by DRFM, and the system delay time is controlled by the FPGA chip. According to the target's radar cross section (RCS), the radar echo cancelling wave will be generated by the FPGA and DRFM on signal processing. The effect of error on the cancelling wave is analysed and the method for reducing nonlinear phase errors is presented. Theoretical analysis and simulation show that the system effectively reduces the signal power received by the radar receiver. Numerical simulation results show that about 11.3 dB target gain reduction can be achieved under the condition of large deviation.

Shift operator finite-difference time-domain (SO-FDTD) method is developed to study the stealth technology of inhomogeneous magnetized plasma in this paper. The high accuracy and efficiency of this method is verified by computing the reflection and transmission coefficients of electromagnetic wave through a collisional magnetized plasma slab in one dimension. The stealth effect of radar targets covered with Epstein distribution inhomogeneous magnetized plasma is studied. The results show that the stealth effect of radar targets covered with Epstein distribution inhomogeneous magnetized plasma is better than that of radar targets covered with homogeneous magnetized plasma.

Summary Phase information of a coherent signal is recorded and preserved as complex data. Although Fourier spectrum has long been proven to be effective, it is sometimes difficult to properly estimate phase information from severely corrupted signals. We present and define two useful parameters: spectral correlation coefficient (SCC) and spectral covariance to mean power ratio (SCR). A simulation test was carried out using a random Gaussian phase noise. The SCC and SCR decrease linearly with extremely low gradients as the noise level increase, and especially the SCC maintains high values larger than 0.9 up to 80% noise corrupted signals. We applied the SCC method to a radar interferometric phase, and demonstrated that it was effective even for severely corrupted signals by noises.