Abstract
Radar signal processing mainly focuses on target detection, classification, estimation, filtering, and so on. Compressed sensing radar (CSR) technology can potentially provide additional tools to simultaneously reduce computational complexity and effectively solve inference problems. CSR allows direct compressive signal processing without the need to reconstruct the signal. This study aimed to solve the problem of CSR detection without signal recovery by optimizing the transmit waveform. Therefore, a waveform optimization method was introduced to improve the output signal-to-interference-plus-noise ratio (SINR) in the case where the target signal is corrupted by colored interference and noise having known statistical characteristics. Two different target models are discussed: deterministic and random. In the case of a deterministic target, the optimum transmit waveform is derived by maximizing the SINR and a suboptimum solution is also presented. In the case of random target, an iterative waveform optimization method is proposed to maximize the output SINR. This approach ensures that SINR performance is improved in each iteration step. The performance of these methods is illustrated by computer simulation.
Highlights
Waveform design is the key aspect of multiple-input multiple-output (MIMO) radar research, since the performance of MIMO radar depends on the specific signal design
We propose in this paper a waveform optimization method to optimize the signal-to-interference-plus-noise ratio (SINR) of the Compressed sensing radar (CSR) without signal recovery in the scenario where the target signal is corrupted by colored interference and noise with known statistical properties
It can be seen that the iterative method had a significantly better performance than the Unlike method had a significantly better SINR performance than the linear frequency modulation (LFM) waveform
Summary
Waveform design is the key aspect of multiple-input multiple-output (MIMO) radar research, since the performance of MIMO radar depends on the specific signal design. According to the different tasks of MIMO radar, radar performance can be improved by targeted MIMO waveform design. The researchers in [2] investigated the optimization of the full-polarization radar transmission waveform and the receiver response to maximize either target detection or identification performance. Since radar target scenes usually satisfy sparse features, such as only a few aircraft in the vast sky, researchers have come to believe that compression sensing technology can be applied to radar signal processing. It is of great practical significance to study the optimal detection of compressed measurement signals in interference environments [1].
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