A comprehensive and well-structured review on the application of deep learning (DL) based algorithms, such as convolutional neural networks (CNN) and long-short term memory (LSTM), in radar signal processing is given. The following DL application areas are covered: i) radar waveform and antenna array design; ii) passive or low probability of interception (LPI) radar waveform recognition; iii) automatic target recognition (ATR) based on high range resolution profiles (HRRPs), Doppler signatures, and synthetic aperture radar (SAR) images; and iv) radar jamming/clutter recognition and suppression. Although DL is unanimously praised as the ultimate solution to many bottleneck problems in most of existing works on similar topics, both the positive and the negative sides of stories about DL are checked in this work. Specifically, two limiting factors of the real-life performance of deep neural networks (DNNs), limited training samples and adversarial examples, are thoroughly examined. By investigating the relationship between the DL-based algorithms proposed in various papers and linking them together to form a full picture, this work serves as a valuable source for researchers who are seeking potential research opportunities in this promising research field.

In this paper, we discuss the ambiguity function (AF) synthesis problem for unimodular sequences, which are widely used in radar/sonar and communication systems. Notions of discrete-time ambiguity function and discrete ambiguity function (DAF) are defined, and the corresponding properties are also discussed for unimodular sequences. Depending on these properties, two algorithms are proposed to synthesize the DAF of the unimodular sequence by minimizing the squared error between a desired complex/real function and a realizable one over $L$ -phase alphabet. To break the volume invariant constraint of a single sequence’s AF, multi-sequences are also considered to be optimized simultaneously to suppress sidelobes of ambiguity surface. Numerical examples show the effectiveness of the proposed algorithms in synthesizing unimodular sequence with a desired AF, and typical polyphase sequences can be well approximated by eight-phase unimodular sequences from the viewpoint of DAF.

With increased degrees of freedom of the transmitter, a coherent waveform-agile radar system can change its interpulse waveform to enhance the capability against increasingly sophisticated jamming and spoofing threats. Furthermore, radar agile waveform can provide better detection performance than a single waveform. In this paper, we consider discrete phase coded sequence set design (DPCSSD) problem based on range-Doppler discrete ambiguity function (RDDAF) for coherent waveformagile radar system. DPCSSD problem for optimizing discrete phase coded sequence set under constant module constraint with desired minimized sidelobes on range-Doppler plane, is a quartic function and the constraint is non-convex. To solve this quartic optimization problem, we propose an effective algorithm based on alternating direction method of multipliers (ADMM), which is a powerful mathematical tool of the augmented Lagrangian scheme for dealing with separable objective functions. As the quartic optimization problem is hard to solve, Majorization- Minimization (MM) is also considered to introduce a quadratic auxiliary function which is the upperbound of the original function. By minimizing the auxiliary function, the original DPCSSD optimization problem can be solved through MM in an iterative way. Meanwhile, the problem of minimizing the quadratic auxiliary function with constraints can be solved through ADMM algorithm. In particular, fast implementation for the most computationally demanding step of matrix inversion is investigated. The effectiveness of the proposed approach is demonstrated via computer simulations.

By repeatedly sampling, storing, and retransmitting parts of the radar signal, interrupted sampling repeater jamming (ISRJ) based on digital radio frequency memory (DRFM) can produce a train of secondary false targets symmetrical to the main false target, threatening to mislead or deceive the victim radar system. This paper proposes a computationally-effective method to estimating the parameters for ISRJ by resorting to the framework of alternating direction method of multipliers (ADMM). Firstly, the analytical form of pulse compression is derived. Then, for the purpose of estimating the parameters of ISRJ, the original problem is transformed into a nonlinear integer optimization model with respect to a window vector. On this basis, the ADMM is introduced to decompose the nonlinear integer optimization model into a series of sub-problems to estimate the width and number of ISRJ’s sample slices. Finally, the numerical simulation results show that, compared with the traditional time-frequency (TF) method, the proposed method exhibits much better performance in accuracy and stability.

In Video synthetic aperture radar (Video SAR) system, the moving target will leave a shadow at its actual position due to Doppler effect. As the shadow of the moving target moves between Video SAR frames, the amplitudes of pixel points at the corresponding positions will jump between frames as well. According to this characteristic, a new method of Video SAR ground moving target detection and tracking based on the inter-frame amplitude temporal curves is proposed in this paper. In this method, the specially designed multiple receptive field fusion neural network model based on frame variation (MRFN-FV) is used to classify the pixel points with obvious inter-frame amplitude jumps on the whole-time axis, and then the false alarms are suppressed based on the temporal change characteristics of pixel points. Finally, the improved clustering algorithm is used to detect, locate and track the moving targets in each frame of SAR images. The effectiveness of the proposed method is verified through the measured data recorded by the THz band Video SAR system.

This letter deals with a novel transmitted scheme for a multisubcarrier frequency multiple-input multiple-output (MIMO)-synthetic aperture radar (SAR) system, which aims at suppressing the intrapulse repeater mainlobe-jamming and immensely improving the dynamic range of the receiver. To this end, due to the multisubcarrier frequency transmission scheme, the mixed signal with true target signal and repeater jamming can be separated by a well-designed spatial-frequency filter. Thus, the range and direction of arrival (DOA) information is accurately estimated without interrupting the normal work of the radar. Furthermore, to further improve the orthogonality of transmitted waveform, the design of a phase-coded LFM waveform pair exhibiting both low cross correlation energy (CCE) and low peak to sidelobe ratios (PSLRs), is considered. Besides, to handle the resulting nondeterministic polynomial (NP) hard problem, an alternating direction multiplier method (ADMM) based optimization method is employed. Compared with the traditional jamming suppression method, the proposed method improves the degree of freedom (DOF) from the carrier frequency domain, and it has the capability to suppress the intrapulse repeater mainlobe-jamming. Finally, detailed simulation experiments are carried out to verify the practicability and effectiveness of the newly proposed transceiver schemes.