功率受限的常规波束形成后处理拟合方法

针对水下目标方位超分辨估计问题,提出一种功率受限(Power Constraint)的常规波束形成(Conventional BeamForming)拟合算法(PC-CBF)。PC-CBF算法通过常规波束形成获得目标方位谱数据,利用阵列响应向量对方位谱进行后处理,准确估计目标个数与目标方位。算法对接收信号的功率进行限制,获得对方位谱的欠拟合,利用凸优化进行反演卷积,估计目标的方位信息。仿真结果表明,算法性能在分辨率上优于基于半正定规划的常规波束形成算法(semi-definite programming Conventional BeamForming,sdp-CBF)和多重信号分类(MUltiple SIgnal Clasification,MUSIC)。对水池实验数据以及湖试数据处理结果显示,PC-CBF算法能够获得较窄的谱峰宽度以及较低的背景级,具有较强的方位估计分辨能力。 

Power constraint conventional beamforming post-processing fitting method

Aiming at the problem of super-resolution estimation of underwater target azimuth,a Power Constraint Conventional BeamForming Fitting algorithm (PC-CBF) is proposed.The PC-CBF algorithm obtains the target azimuth spectrum data by conventional beamforming,and uses the array response vector to post-process the azimuth spectrum to accurately estimate the target number and target orientation.The algorithm limits the power of the received signal,obtains the under-fitting result of the azimuth spectrum,and uses the convex optimization to perform the inverse convolution to obtain the orientation information of the target.The simulation results show that the performance of the algorithm is better than the semi-definite programming Conventional Beamforming (sdp-CBF) and MUltiple SIgnal Classification (MUSIC).The experimental data processing results of the pool show that the PC-CBF algorithm can obtain a narrow spectrum peak width and a low background level,and has a strong azimuth estimation ability.