Considering a new type of netted radar system, the receiver can process the reflected echoes transmitted by all transmitters. Compared with networked radar system, power and beam resources of netted radar system are still limited, and more importantly, the number of transmitting and receiving (TR) beams has increased dramatically. In this letter, a joint transmitter/receiver beam selection and power allocation (JTRBS-PA) strategy is developed for multiple targets tracking in netted radar system. The JTRBS-PA strategy utilizes the target prior information and predicted accuracy to optimize the TR beam selection and the power of each transmitting beam, which aims to maximize target tracking performance under limited radar system resources. A two-step solution technique is proposed to deal with the coupled bivariate constrained optimization problem. Simulation results demonstrate the effectiveness and superiority of the proposed strategy.

It is well-known that for a maneuvering target, its inverse synthetic aperture radar (ISAR) imaging quality may significantly deteriorate using the classical range-Doppler (RD) algorithm. To address this issue, this article proposes a novel ISAR imaging algorithm based on the generalized second-order time-scaled transform (GSOTST). In the proposed method, the multicomponent cubic phase signal (CPS) modeling is adopted for the radar echo signal after translational motion compensation (TMC) to portray the phase change characteristics more accurately. First, the target signal is transformed into the slow-time-delay-time domain using a correlation kernel function (CKF). Subsequently, the nonstationary phase is eliminated in the slow-time-generalized delay-time-frequency (GDTF) domain, and the GSOTST is used to decouple the temporal variables. Finally, the generalized Fourier transform is performed to transform the signal into the 2-D frequency domain, where the energy of the target signal is integrated into a well-focused 2-D peak, enabling the high-precision target parameter estimation and finely focused ISAR imaging. The experimental results from both simulation and real-measured data validate the effectiveness of the proposed algorithm.

This letter proposes a fast Doppler parameter estimation and refocusing method for ground moving targets in a synthetic aperture radar (SAR) system. In the proposed method, after implementing the main-lobe clutter rejection by using the azimuth adaptive processing technique, the range-azimuth positions of smeared target scatterers can be obtained via the constant false alarm rate (CFAR) detection. Then, an autocorrelation function is constructed to transform a moving target signal into the time-frequency plane, where the target parameters can be precisely and efficiently estimated by applying the scaled fast Fourier transform (FFT). Finally, ground moving targets can be well refocused and relocated in a SAR imagery. Compared with the conventional methods, the target output SNR can be enlarged about 3 dB under the low SNR by using the proposed parameter estimation method.

Abstract In this study, a novel fast wideband direction of arrival (DOA) estimation algorithm is proposed to reduce the computational complexity. First, a multiple measurement vector (MMV)‐based compact structure for a wideband signal is established. Combined with the focus operation, the array manifolds of different frequency bins are transformed into the dictionary of the reference frequency. Then, two efficient novel methods named adaptive step‐size‐based null space tuning with hard thresholding and feedback (ASNHF) and MMV‐ASNHF are proposed to process single measurement vector and MMV problem, respectively. Finally, wideband DOA estimation can be achieved by MMV‐ASNHF algorithm. Compared with other algorithms, the proposed algorithm has higher accuracy at a low signal‐to‐noise ratio and lower computational complexity. Simulation results show that the proposed estimator is effective and feasible.

Wide-band interference (WBI) is a critical issue for synthetic aperture radar (SAR), which may severely affect the imaging quality of SAR systems. To suppress WBI effectively, a novel interference suppression algorithm based on robust principal component analysis (RPCA) in time-frequency-pulse (TF-P) domain is proposed. For SAR echoes in TF-P domain, there are two useful properties: 1) The TF characteristic of useful signal in adjacent pulse are similar, indicating that useful signal has low-rank property; 2) Due to its variation of position and sparsely distrusted in TF-P domain, WBI has sparse characteristic. According to these properties, RPCA method is applied to decompose the TF-P matrix into a low-rank matrix (i.e. useful signal) and a sparse matrix (i.e. WBI). Finally, the WBIs can be reconstructed and subtracted from the echoes to realize the interference suppression. The experimental results of simulated data demonstrate that the proposed algorithm not only can suppress interference effectively, but also preserve the useful information as much as possible.

A mainlobe maintenance method based on shrinkage estimator is presented here to promote the adaptive digital beamforming performance when there exists mainlobe jamming (MLJ). First, block matrix preprocessing (BMP) method is applied to suppress the MLJ. Then, the linear combination of estimated covariance matrix and identity matrix is optimised to generate more accurate estimation of the covariance matrix. After that, the improved covariance matrix is utilised to generate the adaptive weights to suppress the sidelobe jamming. Finally, the simulation shows that the proposed method is capable of eliminating peak offset of mainlobe and high sidelobes introduced by BMP and provides robustness against finite data samples effects. Accordingly, it outperforms noise whitening with error compensation, diagonal loading, and robust covariance matrix reconstruction in output SINR.

In the aforementioned letter, the authors indicate that with a$2M + 1$sensor uniform linear array (ULA), up to$2M - 1$sources can actually be localized by the proposed algorithm. In this comment, however, we prove that the algorithm will no longer be valid if the number of sources exceeds$M$. A numerical simulation is performed to verify this conclusion.

Weak-target detection and imaging are the challenging problems of airborne or spaceborne early warning radar. The envelope of a high-speed weak target after range compression spreads over range during the long observation period. To finely refocus a high-speed weak maneuvering target, motion parameters should be accurately obtained for compensating the envelope. This letter proposes a new imaging approach for high-speed maneuvering targets without a priori knowledge of their motion parameters. In this method, the azimuth compression function is constructed in a range and azimuth 2-D frequency domain, which can eliminate the coupling effect between range and azimuth. Theoretical analysis confirms that the methodology can precisely focus targets. Simulation results show that the proposed algorithm improves the performance for detecting and imaging high-speed maneuvering targets.

Multiple access interference (MAI) is a key problem in DS-CDMA. Both the multiuser detection method and antenna array technique have been introduced to reduce the effect of MAI respectively. In this paper, combining wavelet networks with a space-time filter, we propose a novel multiuser detector (MUD). The complexity of the MUD only depends on that of the wavelet networks. With numerical simulations and performance analysis, it is shown that the MUD precedes the conventional Rake receiver and the space-time matched filter in eliminating MAI and near-far resistance.