In this paper, we proposed a monopulse forward-looking high-resolution imaging algorithm based on adaptive iteration for missile-borne detector. Through iteration, the proposed algorithm automatically selects the echo signal of isolated strong-scattering points from the receiving echo signal data to accurately estimate the actual optimal monopulse response curve (MRC) of the same distance range, and we applied optimal MRC to realize the azimuth self-focusing in the process of imaging. We use real-time echo data to perform error correction for obtaining the optimal MRC, and the azimuth angulation accuracy may reach the optimum at a certain distance dimension. We experimentally demonstrate the validity, reliability and high performance of the proposed algorithm. The azimuth angulation accuracy may reach up to ten times of the detection beam-width. The simulation experiments have verified the feasibility of this strategy, with the average height measurement error being 7.8%. In the out-field unmanned aerial vehicle (UAV) tests, the height measurement error is less than 2.5 m, and the whole response time can satisfy the requirements of a missile-borne detector.

本文提出了一种基于自适应迭代的单脉冲前视高分辨率成像算法。通过迭代，该算法自动从接收到的回波信号数据中选择孤立的强散射点的回波信号，以准确估计相同距离范围内的实际最佳单脉冲响应曲线（MRC），并应用最佳MRC来实现方位角在成像过程中进行自我聚焦。我们使用实时回波数据进行纠错以获得最佳的MRC，并且方位角精度在一定距离范围内可能达到最佳。我们通过实验证明了该算法的有效性，可靠性和高性能。方位角精确度可能达到检测光束宽度的十倍。仿真实验证明了该策略的可行性，平均高度测量误差为7.8％。在外场无人机测试中，高度测量误差小于2.5 m，整个响应时间可以满足导弹探测器的要求。