Passive bistatic radar detects targets by exploiting available local broadcasters and communication transmissions as illuminators, which are not designed for radar. The signal usually contains a time-varying structure, which may result in high-level range ambiguity sidelobes. Because the mismatched filter is effective in suppressing sidelobes, it can be used in a passive bistatic radar. However, due to the low signal-to-noise ratio in the reference signal, the sidelobe suppression performance seriously degrades in a passive bistatic radar system. To solve this problem, a novel mismatched filtering algorithm is developed using worst-case performance optimization. In this algorithm, the influence of the low energy level in the reference signal is taken into consideration, and a new cost function is built based on worst-case performance optimization. With this optimization, the mismatched filter weights can be obtained by minimizing the total energy of the ambiguity range sidelobes. Quantitative evaluations and simulation results demonstrate that the proposed algorithm can realize sidelobe suppression when there is a low-energy reference signal. Its effectiveness is proved using real data.

无源双基地雷达通过利用非雷达专用的本地广播公司和通信传输作为照明器来检测目标。信号通常包含随时间变化的结构，这可能会导致高级范围模糊度旁瓣。由于失配滤波器可有效抑制旁瓣，因此可用于无源双基地雷达。但是，由于参考信号中的信噪比低，旁瓣抑制性能在无源双基地雷达系统中会严重降低。为了解决这个问题，使用最坏情况的性能优化开发了一种新颖的失配滤波算法。该算法考虑了参考信号中低能级的影响，并基于最坏情况下的性能优化建立了新的成本函数。通过这种优化，可以通过使歧义范围旁瓣的总能量最小来获得失配的滤波器权重。定量评估和仿真结果表明，该算法可以在低能量参考信号下实现旁瓣抑制。使用实际数据证明了其有效性。