Li Chun-Xiao, Guo Ming-Fei, Zhao Hang-Fang
College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China.
Key Laboratory of Special Purpose Equipment and Advanced Processing Technology, Ministry of Education and Zhejiang Province, Zhejiang University of Technology, Hangzhou 310023, China.
Sensors (Basel). 2020 May 16;20(10):2844. doi: 10.3390/s20102844.
Matched filtering is widely used in active sonar because of its simplicity and ease of implementation. However, the resolution performance generally depends on the transmitted waveform. Moreover, its detection performance is limited by the high-level sidelobes and seriously degraded in a shallow water environment due to time spread induced by multipath propagation. This paper proposed a method named iterative deconvolution-time reversal (ID-TR), on which the energy of the cross-ambiguity function is modeled, as a convolution of the energy of the auto-ambiguity function of the transmitted signal with the generalized target reflectivity density. Similarly, the generalized target reflectivity density is a convolution of the spread function of channel with the reflectivity density of target as well. The ambiguity caused by the transmitted signal and the spread function of channel are removed by Richardson-Lucy iterative deconvolution and the time reversal processing, respectively. Moreover, this is a special case of the Richardson-Lucy algorithm that the blur function is one-dimensional and time-invariant. Therefore, the iteration deconvolution is actually implemented by the iterative temporal time reversal processing. Due to the iterative time reversal method can focus more and more energy on the strongest target with the iterative number increasing and then the peak-signal power increases, the simulated result shows that the noise reduction can achieve 250 dB in the "ideal" free field environment and 100 dB in a strong multipaths waveguide environment if a 1-ms linear frequency modulation with a 4-kHz frequency bandwidth is transmitted and the number of iteration is 10. Moreover, the range resolution is approximately a delta function. The results of the experiment in a tank show that the noise level is suppressed by more than 70 dB and the reverberation level is suppressed by 3 dB in the case of a single target and the iteration number being 8.
匹配滤波因其简单易行而在主动声纳中得到广泛应用。然而，其分辨率性能通常取决于发射波形。此外，其检测性能受到高旁瓣的限制，并且在浅水环境中，由于多径传播引起的时间扩展，性能会严重下降。本文提出了一种名为迭代反卷积 - 时间反转（ID - TR）的方法，该方法对互模糊函数的能量进行建模，它是发射信号的自模糊函数能量与广义目标反射率密度的卷积。同样，广义目标反射率密度也是信道扩展函数与目标反射率密度的卷积。发射信号引起的模糊和信道扩展函数分别通过理查森 - 卢西迭代反卷积和时间反转处理来消除。此外，这是理查森 - 卢西算法的一种特殊情况，即模糊函数是一维且时不变的。因此，迭代反卷积实际上是通过迭代时间反转处理来实现的。由于迭代时间反转方法能够随着迭代次数的增加将越来越多的能量聚焦在最强目标上，进而峰值信号功率增加，模拟结果表明，如果发射一个具有4kHz频率带宽的1ms线性调频信号且迭代次数为10，在“理想”自由场环境中降噪可达250dB，在强多径波导环境中可达100dB。此外，距离分辨率近似为一个狄拉克函数。在水槽中的实验结果表明，在单个目标且迭代次数为8的情况下，噪声水平被抑制超过70dB，混响水平被抑制3dB。
