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This study aimed to investigate the performance of Multicarrier Phase Coding (MCPC) and P4-encoded waveforms. Researchers explored the unique properties of these signals, focusing on aspects like phase distribution, autocorrelation, power spectral density for P4 encoding, and aperiodic autocorrelation and ambiguity function for MCPC signals. The findings identified optimal MCPC sequences with reduced peak-to-mean envelope power ratios (PMEPR), improving signal performance. Complementary codes based on permutation were also generated and analyzed for MCPC sequences. The study utilized an improved genetic algorithm to develop new and improved waveforms, underscoring the importance of techniques like optimal sequence permutation, complementary sequences, and classical window frequency weighting in enhancing signal performance. [ABSTRACT FROM AUTHOR]

This study developed a novel S-band radar system for planar location applications. High-resolution range imaging and target angle estimation were achieved by using a stepped frequency continuous wave (SFCW) signal and single input multiple output (SIMO) architecture with a linear sparse array layout, respectively. An improved time-frequency method was utilized to link the independent range profile and angle spectrum results to obtain the plane positions of the targets. The radar hardware was composed of the antenna array with one transmit element and five receive elements, an RF transceiver, and a signal processing component. Under the proposed waveform parameters and signal processing scheme, a 16-ms process cycle, 0.3-m ranging error, and 0.4° angle estimation error for target positioning were achieved in field tests. These results demonstrate the effectiveness and advantages of the proposed radar system. [ABSTRACT FROM AUTHOR]

With the increasing complexity of the electromagnetic environment and the continuous development of radar technology, more and more modern digital programmable radars using agile waveform will appear in the future battlefield. It is difficult to effectively identify these radar emitters with complex system only by relying on traditional recognition models. In response to the above problem, this paper proposes a recognition method of radar emitters with agile waveform based on hybrid deep neural network and attention mechanism to deal with the problem of variable conventional characteristic parameters of radar emitter signals with agile waveform. First, we perform a distributed representation of the pulse signal data to generate high-dimensional sparse signal features. Then we design to use a dynamic Convolutional Neural Network to extract features of structural details of radar emitter signals with agile waveform at different levels, and use a Long Short-Term Memory to extract its timing features. In order to obtain the deep features that can characterize the agility of the waveform, the attention mechanismbased method is used to fuse the extracted structural features and timing features, and at the same time it can reduce the influence of noise in complex electromagnetic environment on the characteristic data of radar emitter. Finally, the deep feature is input into the Softmax layer to complete the recognition of radar emitters with agile waveform. The experimental results show that the method proposed in this paper can effectively solve the problem of the recognition of radar emitters with agile waveform, and the recognition accuracy is improved by 1.26% compared with the traditional models and other deep models. [ABSTRACT FROM AUTHOR]

In this paper, an additional degree of freedom in phased multi‐input multi‐output (phased‐MIMO) radar with any arbitrary desired covariance matrix is proposed using space‐time codes. By using the proposed method, any desired transmit covariance matrix in MIMO radar (phased‐MIMO radars) can be realized by employing fully correlated base waveforms such as phased‐array radars and simply extending them to different time slots with predesigned phases and amplitudes. In the proposed method, the transmit covariance matrix depends on the base waveform and space‐time codes. For simplicity, a base waveform can be selected arbitrarily (ie, all base waveforms can be fully correlated, similar to phased‐array radars). Therefore, any desired covariance matrix can be achieved by using a very simple phased‐array structure and space‐time code in the transmitter. The main advantage of the proposed scheme is that it does not require diverse uncorrelated waveforms. This considerably reduces transmitter hardware and software complexity and cost. One the receiver side, multiple signals can be analyzed jointly in the time and space domains to improve the signal‐to‐interference‐plus‐noise ratio. [ABSTRACT FROM AUTHOR]

In the conventional frequency diverse array (FDA) radar designs, generalized likelihood ratio test (GLRT) detection utilizes coherent pulses. However, the impacts of an FDA multiple-input multiple-output (FDAMIMO) radar system for detection with incoherent pulses have not been systematically investigated. In this paper, we present an incoherent square-law detector to analyse the performance of both the coherent and non-coherent airborne FDA-MIMO radars in a Neyman-Pearson sense. Moreover, the closed-form expressions of an incoherent square-law detector for the FDA-MIMO radars are derived. For a coherent FDA-MIMO radar, the optimal performance is achieved at a high signal-to-noise ratio (SNR), whereas the superiority of a non-coherent FDA-MIMO radar in distinguishing range dependent targets is validated. The corresponding theoretical derivations are verified by the extensive numerical results to show an improved performance. [ABSTRACT FROM AUTHOR]

At present, multiple input multiple output radars offer accurate target detection and better target parameter estimation with higher resolution in high‐speed wireless communication systems. This study focuses primarily on power allocation to improve the performance of radars owing to the sparsity of targets in the spatial velocity domain. First, the radars are clustered using the kernel fuzzy C‐means algorithm. Next, cooperative and noncooperative clusters are extracted based on the distance measured using the kernel fuzzy C‐means algorithm. The power is allocated to cooperative clusters using the Pareto optimality particle swarm optimization algorithm. In addition, the Nash equilibrium particle swarm optimization algorithm is used for allocating power in the noncooperative clusters. The process of allocating power to cooperative and noncooperative clusters reduces the overall transmission power of the radars. In the experimental section, the proposed method obtained the power consumption of 0.014 to 0.0119 at K = 2, M = 3 and K = 2, M = 3, which is better compared to the existing methodologies—generalized Nash game and cooperative and noncooperative game theory. [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]

We propose 8.2‐GHz band radar RFICs for an 8 × 8 phased‐array frequency‐modulated continuous‐wave receiver developed using 65‐nm CMOS technology. This receiver panel is constructed using a multichip solution comprising fabricated 2 × 2 low‐noise amplifier phase‐shifter (LNA‐PS) chips and a 4ch RX front‐end chip. The LNA‐PS chip has a novel phase‐shifter circuit for low‐voltage operation, novel active single‐to‐differential/differential‐to‐single circuits, and a current‐mode combiner to utilize a small area. The LNA‐PS chip shows a power gain range of 5 dB to 20 dB per channel with gain control and a single‐channel NF of 6.4 dB at maximum gain. The measured result of the chip shows 6‐bit phase states with a 0.35˚ RMS phase error. The input P1 dB of the chip is approximately –27.5 dBm at high gain and is enough to cover the highest input power from the TX‐to‐RX leakage in the radar system. The gain range of the 4ch RX front‐end chip is 9 dB to 30 dB per channel. The LNA‐PS chip consumes 82 mA, and the 4ch RX front‐end chip consumes 97 mA from a 1.2 V supply voltage. The chip sizes of the 2 × 2 LNA‐PS and the 4ch RX front end are 2.39 mm × 1.3 mm and 2.42 mm × 1.62 mm, respectively. [ABSTRACT FROM AUTHOR]

The paper discusses the structure of a distributed radar system for detecting and locating airborne objects. We touch the theoretical problems of designing sector surveillance radars using electronic scanning and rho-theta method. The location is performed by matching the data from two small radars. This improves the accuracy of the moving object trajectory measurements. We present implemented scenarios (parallel or serial) for the layout of two radars in a distributed measurement system based on X-band mobile radars. Mobile radars for remote registration of small airborne object movement parameters are build according to the cascaded active phased waveguide-slot antenna array technology. We discuss the main technical characteristics of radars in a distributed measurement/registration system, determining the limitations on the measurement distance and angular coverage. [ABSTRACT FROM AUTHOR]

Orthogonal frequency division multiplexing (OFDM) based radar systems have recently attracted a lot of research interest. However, demonstration of OFDM radar's capability for target detection using real data is not reported in the open literature. In this work, we demonstrate a method to employ OFDM radar for small boat detection. For this objective, we propose a technique to generate radar return for OFDM waveform using collected radar return data when stepped frequency waveform is transmitted. We, then, derive system model for the estimated radar return data specific to OFDMwaveform. Further, a detection test is proposed for the derived signal model and surveillance environment. Close match between the derived analytical expressions and simulation results validates the proposed detector's performance. [ABSTRACT FROM AUTHOR]

In this paper, we proposed two waveform design methods based on game theory to address the problem of radar detection performance degradation in electronic warfare. Since radar and jammer are completely hostile, their interaction is modeled as two-person zero-sum game. Signal-to-Interference-plus-Noise Ratio (SINR) criterion is used in formulating the utility functions. The existence of Nash equilibrium in games is verified by mathematical derivation. Different game waveform strategies are designed for different information levels of radar and jammer. Iterative water-filling method and two-step waterfilling method are designed to achieve Cournot equilibrium and Stackelberg equilibrium, respectively. Simulation results reveal that game strategies can bring higher radar detection performance than No game signal, especially when jammer power is lower than radar power. Radar detection probability based on game theory can be increased by up to 10% without changing the power. This demonstrates game strategies have great potentials for radar waveform design in electronic warfare. [ABSTRACT FROM AUTHOR]

The coexistence of radar-sensing and communication systems research has received a surge of interest in recent times to tackle the issue of spectrum inadequacy. Designing an optimized radar waveform for a coexistence scenario has been a challenging task for accomplishing the convergence of radar-sensing and communication functionalities, without degrading the performance at either end. This paper proposes a novel global optimization-based Spatial Branch and Bound (SBnB) approach to optimize the phase coefficients of a Non-Linear Frequency Modulated (NLFM) waveform in a CRCS framework. In addition, the Modified-Power Ratio Constraint-Cramér–Rao Lower Bound (M-PRC-CRLB), a local optimization-based approach is proposed to optimize the phase coefficients of an NLFM waveform. The spectral energy distribution and auto-correlation characteristics of an NLFM waveform are comprehensively investigated for various values of polynomial order (N) and at different threshold Signal-to-Noise-Ratio (SNR) values. To compare the proposed waveform design approaches (M-PRC-CRLB, SBnB) with the existing waveform design approaches namely, Minimum Estimation Error Variance (MEEV) and PRC- CRLB, a Peak-to-Side-Lobe-Ratio (PSLR), and Integrated-Side-Lobe-Ratio (ISLR) are evaluated at various polynomial orders and threshold SNR values. Furthermore, the performance of a CRCS is assessed using the radar estimation rate and communication data rate. The simulation results reveal that the proposed optimized radar waveform design approaches provide improved performance compared to the existing radar waveform design approaches in terms of radar estimation rate. Further, the proposed global optimization-based SBnB approach achieves a comparable performance of the communication data rate. In addition, the proposed approaches accomplish enhanced spectral utilization, controlled side-lobe energy levels, reduced range-domain ambiguities, and a higher information rate in a CRCS. [ABSTRACT FROM AUTHOR]

Among the various research branches in multiple-input multiple-output (MIMO) radar, Direction finding is an interesting topic and has attracted extensive concerns. However, many previous strategies are only effective to deal with scenarios without model error, such as well-calibrated sensor array, which is unrealistic in practice. This paper revisits the direction finding issue in a bistatic MIMO radar, in which the direction-dependent mutual coupling (MC) effect in both the transmitting array and the receiving array are considered. An estimator based on parallel factor (PARAFAC) decomposition is introduced. Benefit from the fact that the multidimensional structure of the tensor measurement can be explored, the proposed PARAFAC estimator can offer closed-form solution to direction finding without additional pairing calculation, so it is much more accurate and efficient than the state-of-the-art spectrum search method and the rotational invariance algorithm. The improved PARAFAC approach is mathematically analyzed in detail, Several computer trials are carried out to show the theoretical advantages. [ABSTRACT FROM AUTHOR]

Whenever more than one target exist, the most important problem is to associate associating the received signals to the correct targets. This problem appears for all multiple target applications such as multiple target tracking and it is known as "Data Association ". For frequency-based systems, Multiple-Input Multiple-Output (MIMO) configuration together with the frequency diversity of the system enable us to determine the number of moving targets by using the Doppler frequencies. These frequencies include all relevant information about the location, velocity and direction of the targets and hence, they can be used efficiently to estimate the unknown target parameters. [ABSTRACT FROM AUTHOR]

In view of the limitation of the range factor on analyzing low probability of intercept (LPI) performance of MIMO radar systems, a performance parameter is derived and applied for quantifying the LPI performance of distributed MIMO radar systems. A series of contour charts have been given with different values of geometrical parameter. By plotting and analyzing these charts, the LPI performance can be obtained intuitively. Simulation results show that LPI performance of distributed MIMO radar systems depends on both radar parameter and system geometry. It is shown that the spatial diversity gain plays an important role in designing a distributed MIMO radar system with robust LPI performance. [ABSTRACT FROM AUTHOR]

The multi-band signal fusion method is a practical and effective technique to improve the range resolution of the radar. This paper proposes a multi-stage approach based on the Generalized Likelihood Ratio (GLR) test for estimating the target range profile using sparse subband measurement data. The proposed subband fusion algorithm estimates, and compensates for the incoherent factors between the subbands, in the first step. In the second step, by combining the data of subbands, the model parameters and the number of scattering centers are estimated based on the Geometrical Theory of Diffraction (GTD) model. Finally, based on the initial values of the model parameters and the incoherent factors obtained in the preceding steps, the GTD model parameters, and the incoherence parameters are re-estimated simultaneously based on the GLR test to improve the parameters' accuracy. In comparison to the conventional methods, where the incoherence parameters and the model parameters are independently estimated, the accuracy of the estimation of the parameters in the proposed method has improved with the simultaneous estimation of these two types of parameters. Also, the proposed method does not require prior information about the number of scattering centers. The validity and performance of this algorithm have been investigated with analytical and simulated data. [ABSTRACT FROM AUTHOR]

The resource allocation strategy plays an important role in the multifunctional performance of distributed multiple-input and multiple-output radar (D-MIMO-R) systems. In applications, different functions may be conflicting, due to the competition of the same resource. In this paper, a bi-objective hybrid particle swarm optimization (BHPSO) algorithm is proposed for the simultaneous optimization of the search and track functions, under the constraint of limited active subarrays and power budget. In the BHPSO, the nonlinear time-varying coefficients are used to balance the exploitation and exploration abilities in different stages. The heuristic mapping scheme is designed to cope with the constraints. The crossover and mutation operators are devised to the break the swarm stagnation. The distance-based crowding function with the local guider scheme is incorporated to preserve the swam diversity. In addition, by exploiting the unique structures of the objective functions, we fully prove that the solutions, each of which corresponds to a specific power budget for the search or track function, have a proportional relationship. Thus, the best-known Pareto subset (BKPS) can be obtained by parallel solving two convex optimization models only once. Extensive simulation results show the effectiveness and efficiency of the proposed BHPSO, in comparison with the state-of-the-art algorithms. The statistical results also indicate that the target reflectivity is a main influence factor on the resource allocation, and the BHPSO can provide competitive results on standard test functions. [ABSTRACT FROM AUTHOR]

The ordered statistics (OS) scheme is an effective constant false alarm rate (CFAR) technique deployed in many radar systems. It is widely deployed because of its simplicity and effectiveness under conditions of both homogeneous and non-homogeneous radar returns. However, the problem of inaccurate censoring typically degrades its performance since it is often difficult to accurately determine the actual number of interfering targets and clutter edges in the reference window per time. In this article, we address this problem based on the principle of discriminant analysis (DA) towards automatically and effectively estimating the k th rank ordered element of the OS scheme. Our scheme, termed the DA-OS scheme, works without requiring a priori knowledge about the statistical characteristics of the input radar returns. The results obtained via Monte Carlo simulation indicate that the DA-OS scheme achieves a small CFAR loss of about 0.392 dB relative to the cell averaging (CA) scheme under conditions of homogeneous radar returns at a probability of detection of 0.5. It outperforms other notable traditional schemes, including the CA, smallest-of CA, greatest-of CA, and the fixed OS schemes under conditions of non-homogeneous radar returns. Finally, it provides a number of desirable qualitative characteristics as against other existing censoring techniques. • A new censoring method is proposed for the ordered statistics (OS) CFAR scheme. • The proposed scheme does not depend on prior information about the radar return. • The BCV metric is used to determine the homogeneity/non-homogeneity of radar returns. • Our scheme outperforms other CFAR schemes such as the CA, SOCA, GOCA, and OS schemes. • Our scheme provides improved characteristics against other censoring schemes. [ABSTRACT FROM AUTHOR]

In light of increasing requirement for electromagnetic spectrum, spectrum efficiency improvement of radar and communication integration waveform is gaining interest. In this paper, to improve conventional linear frequency modulation (LFM)–continuous phase modulation (CPM) spectrum efficiency, a modified radar and communication integration waveform is proposed. Considering high spectral efficiency of shaped-offset quadrature phase-shift keying (SOQPSK), we generate a new modulation: shaped octal phase-shift keying (S8PSK) by combining the precoding method and CPM with octal phase-shift keying (8PSK). S8PSK is then used to encode communication data into LFM radar signal to form a novel radar and communication integration waveform: LFM-S8PSK. Numerical results demonstrate that compared with LFM–CPM, LFM-S8PSK can provide better spectrum efficiency in exchange for slightly worse bit error rate (BER). Also, it is shown that LFM-S8PSK almost maintains comparable radar performance with respect to LFM. [ABSTRACT FROM AUTHOR]