This paper considers jointly optimizing the transmitting (Tx) waveform and the receivers of a multiple-input multiple-output (MIMO) dual-function radar-communication (DFRC) system. The proposed approach incorporates the design of the (complex-valued) communication receiving (Rx) coefficients, in addition to the radar Rx filters. We address the problem of maximizing the minimum radar signal-to-interference-plus-noise ratio (SINR) subject to communication SINR, per-antenna power and peak-to-average-power ratio (PAPR) constraints. A successive convex approximation (SCA) algorithm is developed to find a good solution for the resultant nonconvex design problem. To accelerate that algorithm and to improve the solution quality, we further propose a local-approximation-refinement SCA (LAR- SCA) algorithm which possesses guaranteed convergence properties. In addition, a sub-block design technique is developed to reduce the design complexity in the case of long Tx sequences. Numerical results show that by incorporating the communication Rx coefficients into the joint design, the radar and communication capabilities of the DFRC system can be significantly enhanced over the state-of-the-art designs, while maintaining an efficient algorithm.

Unlike the conventional phased array, the frequency-diverse array (FDA) employs a tiny frequency increment across the array elements, which is capable of providing range–angle–time-dependent beampattern, and thereby offers potential benefits in target localization and interference mitigation. Reported literature on FDA mostly focuses on its intrapulse (fast-time) property and ignores the interpulse (slow-time) feature induced by frequency offset. In this article, incorporating the neglected inherent slow-time coding feature, a novel slow-time FDA multiple-input multiple-output (FDA-MIMO) technique is proposed for the space-time adaptive processing (STAP) radar. The new coding scheme can separate transmitting (Tx) signals via slow-time Doppler filtering, and the problem of signal aliasing is tackled by appropriately designing the slow-time codes. At the receiving (Rx) side, two Rx schemes are devised for recovering range-dependent Tx degrees-of-freedom. Moreover, the relevant clutter rank and the rule for code design are derived in detail. The outstanding merits of the proposed slow-time FDA-MIMO STAP radar consist of the following: There is no specific restriction on the probing waveform; the negative effect of time-variant pattern is perfectly eliminated; and both the target localization accuracy and clutter suppression performance are superior over the state-of-the-art FDA radar systems. Numerical results corroborate the superiorities of the proposed waveform strategy for STAP application.

Traditional phased array-based space-time adaptive processing (STAP) suffers from severe performance degradation in the presence of dense false-target jamming, especially mainlobe deceptive jamming. In this paper, an enhanced 3-D joint domain localized STAP method, incorporated with deceptive jamming pre-whitening in the transmit–receive spatial domain, is proposed to deal with this problem. It exploits the characteristic that the target, clutter, and deceptive jamming are discriminable in the range-angle-Doppler domain of a frequency diverse array multi-input multi-output radar. The designed pre-whitening filter has excellent performance in deceptive jamming mitigation, since it is constructed by the target-free jamming samples which are obtained by a novel strategy of spectrum feature-based jamming sample selection. As a result of taking the advantage of differences among the 3-D spectra of the true target, clutter, and deceptive jamming, the proposed sample selection strategy can extract unpredictable deceptive jamming samples efficiently even in the presence of strong true targets and heavy ground clutter. Signal-to-interference-plus-noise-ratio loss analysis and numerical examples are given to demonstrate the effectiveness of the proposed method in the dense deceptive jamming scenario.

This paper develops a transmit (Tx) waveform de- sign technique for dual-function radar-communication systems that provide both multiple-input multiple-output (MIMO) radar and multi-user multiple-input single-output (MU-MISO) com- munication functionalities. We propose a hybrid linear-nonlinear precoding (HLNP) signaling scheme, in which the dual-use waveform is the superposition of linearly-precoded communica- tion symbols and a nonlinearly-precoded waveform that improves the radar performance. To attain good radar Tx beampattern and waveform ambiguity properties, we focus on optimizing a weighted sum of the integrated main-lobe-to-sidelobe ratio (IMSR) of the Tx beampatttern and a novel angular waveform similarity metric, while ensuring a predefined signal-to-interference-plus- noise ratio (SINR) for each communication user. Practical con- straints are imposed on the Tx waveform, including per-antenna power and peak-to-average-power ratio (PAPR) constraints. We propose an extended feasible point pursuit successive convex ap- proximation (EFPP-SCA) algorithm to solve the resultant non- convex problem and establish its convergence properties. To re- duce the computational cost of designing a long Tx waveform, we further introduce a sub-block design technique. Numerical ex- amples indicate that the proposed HLNP provides a superior performance tradeoff between sensing and communication com- pared to conventional nonlinear precoding.

As a wideband radar system, a synthetic aperture radar (SAR) may conflict with several electromagnetic systems, such as frequency modulation (FM), TV, and other communication systems. These signals, termed as radio frequency interference (RFI), may severely interfere SAR systems from generating a high-resolution image. Numerous previous researches focused on the RFI suppression problem, among which the semiparametric methods have been verified to have the state-of-the-art performance. However, most of the semiparametric methods are computationally expensive and can hardly be used on wide-swath SAR imaging processing. In this article, an efficient semiparametric algorithm is proposed to suppress RFIs via alternating projections. It has comparable performance as the other methods but significantly improves the computational efficiency a lot. It is able to remove both narrowband and wideband RFIs and can be used directly on the Level-1 SAR data. Finally, multiple real SAR data are provided to demonstrate the effectiveness and efficiency of the proposed algorithm.

Synthetic aperture radar (SAR), as a wideband radar system, may be subject to strong interferences with a variety of signals. The narrowband interference (NBI) exemplifies the most typical of its kind, such as the form of radio frequency interference (RFI). With the development of SAR imaging technology, the high-resolution wide-swath (HRWS) imagery technology now reaches its maturity to finally take shape in current SAR systems. To obtain HRWS images, the multichannel SAR (MC-SAR) system has been employed to tackle the contradictory requirements for both high resolution and low pulse repetition frequency (PRF). Previous interference methods focused on single-channel SAR systems and few research works for MC-SAR systems. In this article, we first derive a new interference-mitigation model for HRWS SAR systems and conclude that the low-rank property of the NBI is suitable for MC-SAR systems. Then we employ an image-domain sparse regularization to protect the real echoes of the SAR system and mitigate the NBIs by solving the low-rank recovery problems of NBIs. Also, the MC-SAR system errors are further taken into account as a measure for our method’s practical applicability. Finally, the real SAR data is used to demonstrate the effectiveness of the proposed method.