论文部分内容阅读
针对MTI(Moving Target Identification,动目标显示)脉冲串线性处理方法速度模糊严重的情况,应用BP(Back Propagation,反向传播)神经网络对参差MTI的速度模糊函数进行优化。通过神经网络的非线性映射能力,使MTI参差脉冲串的多普勒响应接近理想的狄拉克函数,从而解决了传统线性方法对于参差脉冲测速的模糊。仿真结果表明,对于某典型6脉冲MTI回波序列,测速精度可达到5m/s。
Aiming at the severe ambiguity of linear moving method of MTI (Moving Target Identification), BP (Back Propagation) neural network is used to optimize the speed fuzzy function of variable MTI. Through the nonlinear mapping ability of neural network, the Doppler response of MTI staggered bursts approaches the ideal Dirac function, thus resolving the ambiguity of the traditional linear method for the jerkiness of jagged pulses. Simulation results show that, for a typical 6-pulse MTI echo sequence, the speed accuracy can reach 5m / s.