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The interrupted-sampling repeater jamming (ISRJ) countermeasure is researched based on waveform agility and mismatched filter design in this work. By analyzing the effects of transmitted waveform on ISRJ imaging characteristic, the principle of the anti-ISRJ method is proposed. The ISRJ range processing gain and energy can be suppressed by designing the waveform and mismatched filter. Meanwhile, the ISRJ azimuth processing gain can be further restrained by utilizing the waveform agility. The anti-ISRJ problem is formulated and is then divided into several subproblems. The analytical solutions of waveform and mismatched filter are derived based on majorization minimization (MM), and a fast algorithm is proposed by applying a squared iterative method (SQUAREM). The fast implementation of the algorithm is derived, and computational complexity is $\mathcal {O}({N\log N})$ . Moreover, to improve the anti-ISRJ performance, the peak-to-average power ratio (PAR) constraint is introduced. Specifically, the waveform design subproblem under PAR constraint is solved, and thus, the PAR waveform can also be designed by the proposed algorithm. The simulation results verify that the proposed joint design algorithm shows significantly faster running speed than the conventional algorithms. The anti-ISRJ performance is superior to the existing methods, and the best anti-ISRJ performance can be obtained by applying the PAR waveform agility and mismatched filter design method.

This paper deals with the joint design of intra-inter agile pulses and Doppler filter banks to improve Doppler ambiguous target detectability in signal-dependent mainlobe clutter. Assuming that the target's range and Doppler frequency (RDF) belong to an uncertainty set and that the clutter knowledge is partially known, a robust processing procedure based on a pulse compression matched filter and Doppler filter banks is proposed for the echo of the pulses with non-uniform pulse repetition interval (PRI). Then, the worst-case signal-to-interference-plus-noise ratio (SINR) at the output of all receive filters as the figure of merit is considered to be optimized along with both peak-to-average power ratio (PAR) constraint and energy constraint on the transmitted pulses. Utilizing an equivalent reformulation of the resultant non-convex maximin optimization problem, a maximum block improvement (MBI) framework that partitions the optimization variable into multiple blocks and updates only the block yielding the maximum increase of the objective function at each iteration, is developed to increase the worst-case SINR monotonically. Each block mainly invokes majorization-maximization (MM), sequential convex approximation (SCA) and entropy mirror descent (EMD) to obtain an enhanced solution. Two design strategies are also developed to seek valuable PRIs. Finally, at the analysis stage, the performance of the proposed robust technique is assessed, showing its capability for Doppler ambiguous target detection in a cluttered environment.

The cross-ambiguity function (CAF) is a crucial performance evaluation metric for transmit waveform. To improve the interference suppression performance in the wireless sensing field, we address the problem of synthesizing radar CAF by jointly designing the transmit waveform and receive filter in this letter. We first establish the joint design problem as a non-convex fractional problem by maximizing the signal-to-interference plus noise ratio (SINR) under practical constraints. To overcome the challenges posed by the peak-to-average ratio (PAR) constraint, we then propose an novel iterative optimization algorithm based on the Majorization-Minimization (MM) framework. This algorithm synthesizes the transmit waveform and receive filter alternately and efficiently. Finally, we conduct numerical simulations with different parameters to demonstrate the effectiveness of our proposed CAF synthesizing algorithm.

To suppress narrow band interferences, sparse frequency wave form can be transmitted by wide band radar systems. It suffers the high range side lobes. Anew algorithm for sparse frequency waveform design with range side lobes constraint is proposed. The approach affords much better frequency stop band suppression by flexibly controlling sidelobes constraint using Weighted integrated sidelobe level (WISL) metric. The approach is computationally efficient and can suit the more general Peak to-average power ratio (PAR) constraint. An extension to Multiple-input multiple-output (MIMO) radar case is also presented.