一种基于距离-方位字典的仿生目标定位方法

Bionic target localization method based on range-azimuth joint dictionary

传统水下声呐系统通常采用增大阵列孔径,增加阵元数目来实现角度高分辨,这势必会导致系统复杂、成本高。鉴于大棕蝙蝠利用简单构架的系统获得了令人惊讶的高分辨能力,本文提出了一种仿生目标定位方法。基于多谐波发射、双随机阵接收的仿生体制构建了距离-方位联合字典,进而分析了字典的相干特性并估计了目标的距离和方位角,最后完成了实验验证。结果表明,基于稀疏表达的仿生距离-方位联合估计能够在回波高混叠条件下实现高精度目标定位。

The traditional underwater sonar system usually achieve high angle resolution by increasing array aperture and the number of array elements,but this method will inevitably lead to complex system and high cost.Given that big brown bats have obtained surprisingly high resolution using a simple system,this paper proposes a bionic target localization method.First,a range-azimuth joint dictionary was constructed based on the bionic system of multi-harmonic emission and double random array reception.Then,the coherence characteristic of the dictionary was analyzed and the range and azimuth of the target were estimated,and at last the experimental verification was completed.The results show that the bionic range-azimuth joint estimation based on sparse signal representation can achieve high-precision target localization under the condition of echo high aliasing.