一种适用于北极双轴声道的改进压缩匹配场定位算法研究

Research on an Improved Compressive Matched Field Localization Algorithm for Arctic Double Channels

北极水域信道特殊,匹配场处理作为一类可结合环境信息进行信号处理的目标定位方法,在模型匹配时可以准确估计出声源位置,但存在环境变化复杂且信息了解少的问题,导致模型很难完全匹配,从而出现位置估计不准确的问题。该文提出建立一种改进的压缩匹配场模型,并基于相位归一化原理对稀疏模型进行优化,利用归一化阵元域信息进行匹配,以消除声源频谱的影响,提高压缩匹配场的定位准确度。仿真结果表明,改进后方法比改进前方法的定位准确率更高;试验数据处理表明,单快拍下改进后方法比改进前方法在目标位置估计上误差更小,比常规匹配场方法的分辨率更高。

Arctic underwater channels are complex.Matched field processing is a kind of target localizing method that can combine environmental information with signal processing methods.The target position can be accurately estimated when model is matched.However,due to the complex environment and the lack of key information,it is difficult to match the model completely,which leads to the problem of inaccurate estimation.In this paper,an improved matched field algorithm is proposed.Based on the principle of phase normalization,the sparse model is optimized,and the normalized information of arrays is used for matching to eliminate the influence of signal spectrum.The simulation result shows that the accuracy of the improved method is higher than that of the former method.The experimental data processing shows that the improved method has less error in target position estimation and higher resolution than the conventional matched field processing method.