摘要
在有限系统瞬时带宽下,针对脉冲压缩处理距离分辨力受限的问题,提出了两种虚拟频带扩展距离维波束形成算法。对接收信号频域输出进行多子带划分并消除自身固有相位,利用子带间对应频点由目标距离带来的相移构成复指数等比数列这一特点,使用划分的子带数据,分别采用线性预测和最小二乘估计两种方法对信号进行虚拟子带预测,其中线性预测以子带频域快拍为单位进行预测,最小二乘估计以子带为单位进行预测,利用扩展后的频带数据构建协方差矩阵,结合距离维波束形成模型获得功率谱。所提两种算法在不改变发射带宽条件下,使回波信号带宽在虚拟意义上得到扩展,均可有效减小距离维主瓣宽度,提高距离分辨性能。数值仿真和湖试数据分析结果验证了算法的有效性。
Two virtual frequency band extension algorithms based on the range-dimensional beamforming method are proposed to enhance the range resolution of pulse compression within the constraints of finite system instantaneous bandwidth.The received signal in the frequency domain undergoes subdivision into multiple sub-band components,and the inherent phase is eliminated.The phase shift induced by the target distance at the corresponding frequency points among the sub-bands forms a complex exponential geometric series.Exploiting this characteristic,linear prediction and least squares estimation are employed for virtual sub-band prediction.Linear prediction operates on frequency domain snapshots within each sub-band,while least squares estimation is performed on the sub-band units.The covariance matrix,constructed from the extended frequency band data,is utilized to derive the power spectrum.These two proposed algorithms can virtually expand the echo signal bandwidth without altering the transmission bandwidth.Additionally,they can effectively reduce the main lobe width in the range dimension and improve the range resolution performance.The efficacy of these algorithms is demonstrated through numerical simulations and lake test data.
作者
李朋卓
马晓川
刘宇
扶钰斌
陈筱月
LI Pengzhuo;MA Xiaochuan;LIU Yu;FU Yubin;CHEN Xiaoyue(Key Laboratory of Information Technology for AUVs,Institute of Acoustics,Chinese Academy of Sciences Beijing 100190;School of Electronic,Electrical and Communication Engineering,University of Chinese Academy of Sciences Beijing 100049)
出处
《声学学报》
北大核心
2025年第2期500-510,共11页
Acta Acustica
基金
国家重点研发计划项目(2022YFC3101900)资助。
关键词
虚拟频带扩展
距离维波束形成
线性预测
最小二乘估计
Virtual bandwidth expansion
Range-dimensional beamforming
Linear prediction
Least squares estimation
