This paper deeply explores the detection of a signal belonging to a union of subspace (UoS) in the presence of interference subspace. We propose three detectors based on the generalized likelihood ratio test (GLRT), Rao criterion, and Wald criterion using the presymmetry structure of the received data. By taking advantage of the data’s presymmetric structure, we can detect the signal more effectively. Experimental results show that the proposed detectors perform better than the traditional detectors in the presence of interference subspace, especially when the training data is insufficient. In general, this paper provides an effective method for solving the problem of signal detection with interference subspace.

This paper presents a cognition-based transmitter polarization optimization method for the conformal array space-time adaptive processing. First, we introduce the signal model and working mechanism of the airborne conformal array radar. Then the polarization characteristics of the target are recognized through the least squares criterion. Leveraging the estimated target scattering matrix, we further design the transmitter polarization optimization problem. Finally, the semidefinite relaxation approach is adopted to obtain the optimized transmit weight vector. Simulation results demonstrate the effectiveness of the proposed method in clutter cancellation.

Doppler ambiguity in missile-borne radar is usually caused by the low pulse-repetition-frequency (PRF) waveforms, which may result in a significant performance loss of target detection and location in the presence of clutter. To solve the issue of Doppler ambiguity clutter in missile-borne space-time adaptive processing (STAP) radar, this paper proposes a novel clutter suppression approach with the aid of designing the pulse interval (PI) of the waveform. Specifically, we formulate the optimization problem by considering the metric of minimizing the maximum sidelobe level in the Doppler domain, subject to the constraint of a given coherent processing interval (CPI).To solve the complicated problem, the modified genetic algorithm combining the simulated annealing algorithm (MGA-SA) is devised. Extensive simulations showcase that the proposed method surpasses SCNR by over 3dB in clutter suppression effectiveness when compared to conventional techniques, all while maintaining the same dwell time and frequency resources.

This paper proposes a reduced-dimension polarization-space-time adaptive processing (RD-PSTAP) algorithm for airborne conformal array (CFA) radar to achieve better clutter suppression performance at lower computational complexities. Firstly, we take polarization information into signal modeling. Subsequently, the dimension reduction matrix is derived based on the generalized sidelobe cancellation (GSC) structure, which incorporates the polarization information of the target and clutter into constructing the main channel and auxiliary channels, respectively. Simulation results demonstrate the effectiveness of the proposed algorithm compared with the conventional RD algorithm.

If the pointing directions of antenna elements are inconsis-tent, the received signal of each sensor will vary due to the polarization effect, and this will influence the target detection performance. To analyze this problem, we establish an irreg-ular array structure and give a signal model for this structure. Then we propose a polarimetric detector based on two-step GLRT in Gaussian clutter background. By conducting ex-periments based on simulated clutter data, we prove that the proposed fully adaptive detector has constant false alarm rate (CFAR) property, and the detector has a better performance for low-speed target detection compared with regular array structures.

This letter deals with the adaptive detection problem in compound Gaussian sea clutter with inverse Gaussian texture when the mismatched signal occurs. In order to reject the mismatched signal, we introduce a fictitious signal to the null hypothesis based on the adaptive beamformer orthogonal rejection test (ABORT). We adopt the two-step generalized likelihood ratio test (GLRT) criterion and develop two selective detectors, i.e., the ABORT-like compound Gaussian with inverse Gaussian (A-IGCG) detector and ABORT-like maximuma posteriori(MAP) compound Gaussian with inverse Gaussian (AM-IGCG) detector. Both the proposed detectors are proved to be constant false alarm rate (CFAR) detectors. The several experiments that compare the proposed detectors with other selective detectors and compound Gaussian detectors are conducted by using two types of real sea data, i.e., IPIX 1998 and 2019 real sea data. The numerical results indicate that the novel detectors exhibit significant tradeoffs between performances of detection and selectivity property.

This letter presents the derivation of the generalized likelihood ratio test (GLRT)-based polarimetric detector in the non-Gaussian clutter. We model the non-Gaussian sea clutter as compound-Gaussian distribution with inverse-Gaussian texture (IG-CG), which has better goodness-of-fit for the high-resolution sea clutter. Based on the two-step GLRT criterion, we develop the test statistic of the proposed detector by assuming the texture component is known in the first step. In the second step, with the texture of the secondary data estimated as the power of the clutter, we insert the maximuma posterioriestimate (MAPE) of the texture of the primary data into the test statistic to achieve the fully adaptive detection. Furthermore, the model-based polarimetric detector, which exploits the independence between the co-polarized and the cross-polarized component, is derived. Finally, we conduct experiments with simulated clutter and real sea clutter to evaluate the performance of the proposed detector. The simulation results verify that the proposed detectors have better detection performance and the MAPE under different hypotheses leads to different levels of robustness to the mismatched signal.

This article investigates regularized estimation of Kronecker-structured covariance matrices (CMs) for polarization radar in sea clutter scenarios where the data are assumed to follow the complex elliptically symmetric (CES) distributions with a Kronecker-structured CM. To obtain a well-conditioned estimate of the CM, we add penalty terms of Kullback–Leibler divergence to the negative log-likelihood function of the associated complex angular Gaussian (CAG) distribution. This is shown to be equivalent to regularizing Tyler’s fixed-point equations by shrinkage. A sufficient condition that the solution exists is discussed. An iterative algorithm is applied to solve the resulting fixed-point iterations, and its convergence is proven. In order to solve the critical problem of tuning the shrinkage factors, we then introduce two methods by exploiting oracle approximating shrinkage (OAS) and cross-validation (CV). The proposed estimator, referred to as the robust shrinkage Kronecker estimator (RSKE), is shown to achieve better performance compared with several existing methods when the training samples are limited. Simulations are conducted for validating the RSKE and demonstrating its high performance by using the IPIX 1998 real sea data.

This paper focuses on the problem of coexistence between a colocated multiple-in multiple-out (MIMO) radar and down-link communication systems. We propose an iterative algorithm to minimize the Cramer-Rao Bound (CRB) on the direction of arrival (DOA) of a target, accounting for the energy and similarity constraints. More Specifically, at each iteration of this algorithm, the radar waveform is obtained with the aid of the alternating direction method of multipliers (ADMM) algorithm, and then the communication weights are obtained by exploiting the block successive upper-bound minimization method (BSUM). Finally, numerical results are presented to evaluate the effectiveness of the proposed algorithm.

In this paper, we investigate the problem of transmit beam-pattern design for MIMO radar with one-bit DACs. Based on the Fast Fourier Transform (FFT), we propose an alternating minimization (AM) method to minimize the weighted squared-error (WSE) between the designed beampattern and a given one. In particular, we propose an approximation approach to achieve a high-quality solution with one-bit constraint. Finally, numerical simulations demonstrate that the effectiveness of the proposed method.

Deploying low-resolution (e.g. one-bit) digital-to-analog converters (DACs) is of great importance in the multiple-input multiple-output (MIMO) system equipped with a large-scale antenna array since such a hardware architecture brings low-cost and circuit power saving for each antenna. In this paper, the problem of transmit signal design in a large-scale MIMO system with 1-bit DACs is investigated. To ensure directional transmission, we propose to design the transmit signal by minimizing the weighted mean-squared error (MSE) between the formed beampattern and a given one. The resulting design problem, which involves a nonconvex fourth-order objective and a set of nonconvex discrete constraints, is NP-hard, and therefore, an alternating minimization (AM) method is devised. In order to obtain a high-quality 1-bit solution, we propose a continuous and differentiable function to approximate the 1-bit signal, such that the problem with discrete 1-bit constraint is recast to an unconstrained optimization problem with a penalty term, which can be effectively solved via the limited-memory Broyden, Fletcher, Goldfarb, and Shanno (L-BFGS) approach. Moreover, it is found that a closed-form solution can be obtained when equal weights are applied. In addition, low-complexity schemes are developed based on the fast Fourier transform (FFT). The numerical simulations are conducted to demonstrate the effectiveness and superiority of the proposed method.

This paper investigates the problem of the spectrally compatible waveform design for multiple-in multiple-out (MIMO) radar transmit beampattern formation, subject to peak-to-average-power ratio (PAR) and waveform similarity constraints. Since the formulated optimization problem of minimizing the Integrate Sidelobe Level (ISL) and the waveform energy of the stop-band frequencies is NP-hard, an auxiliary variable is first introduced to modify the non-convex problem into a bi-quasiconvex problem, and then the approximated alternating directions method of multipliers (A-ADMM) algorithm is proposed to tackle the resulting bi-quasiconvex problem. Finally, numerical results are presented to evaluate the effectiveness of the proposed algorithm.

Exploiting Spatial and Doppler nulls is a straightforward way to construct a valid blocking matrix(BM) in the generalized sidelobe canceller(GSC)-based Space-time adaptive processing(STAP). However, spatial nulls of the airborne collocated MIMO radar are not uniformly distributed and their unknown frequencies remain to be estimated. In this work, we develop estimation rules of spatial null for the airborne collocated MIMO radars. The proposed rules provide closed-form solutions of both the number and frequencies of spatial nulls. By using the proposed estimated rules to construct the BM, the resulting GSC-based STAP processor exhibits near-optimum performance and outperforms the conventional estimation rules. Simulations are provided to verify the accuracy of the proposed estimation rule and demanstrate the effectiveness of its application to the GSC-based STAP.

The time difference localization suffers from the performance deterioration of time delay estimation (TDE) due to the presence of clock frequency error in incoherent systems. Based on the modified signal model of TDE, the joint maximum-likelihood (ML) estimation of time delay and system clock frequency error is proposed. Then, the Cramér-Rao lower bounds (CRLBs) of time delay and clock frequency error estimations are given. The performance of time delay estimation may be significantly improved to approach CRLB by proposed method. Further, the accuracy of proposed time delay estimator is unaffected by performance of system clock in moderate condition, that is verified by simulation results.