航空磁探中磁异常信号检测器性能仿真分析

Simulation Analysis of Performance of Magnetic Anomaly Signal Detector for Airborne Magnetic Anomaly Detection

航空磁异常探测中目标信号受到飞行器机动平台的干扰和强背景噪声的影响,使得传统的基于正交基函数分解的检测器虚警率过高不能满足实际应用需求。针对航空磁探中的弱信噪比检测问题,提出了一种基于小波分解变换的能量积累检测算法用于磁异常信号检测以提高检测性能。首先对含噪的航空磁异常信号在输入端进行小波去噪预处理,对提纯后的航空磁异常信号进行流式Mallat小波分解,对分解在各个尺度上比例成分不同的粗分辨逼近能量和代表信号边缘的细节信息能量使用多尺度能量积累器对小波信号能量进行积累,并将积累器得到的总能量信号送入判决器进行判决。采用复杂磁环境下的实测噪声数据对积累器进行性能分析,并同传统的OBF检测器以及航空动目标OBF检测器进行比较。结果表明,小波域多尺度能量积累检测器可以在弱信噪比条件下准确地检测目标。

The target signal in airborne magnetic anomaly detection is severely affected by the interference of the aircraft maneuvering platform and strong background noise. It leads to the large false alarm rate of the traditional detector based on the decomposition of orthogonal basis functions（ OBF）. Thus the detector cannot be applicable to practical requirement. As to the problem that the low signal-to-noise ratio（ SNR） detection for airborne magnetic anomaly,an energy accumulation detection algorithm based on wavelet decomposition transform is proposed for the airborne magnetic anomaly signal detection to improve the detection capability. Firstly,the airborne magnetic anomaly signal corrupted by the noise is processed by the wavelet transform denoising at the input end. The purified airborne magnetic anomaly signal is decomposed by flow-type Mallat wavelet decomposition. Then the energy of coarse-resolution approximation and the energy of detailed information are accumulated at each scale by the multi-scale energy cumulant. The detailed information presents the edge of the signal. The total energy signal from the wavelet domain is sent to the decision device for signal detection. The performance of the cumulant is analyzed by using the measured noise data in the complex magnetic environment and compared with the OBF detector and airborne moving target OBF detector. The results show that the multi-scale energy cumulant in wavelet domains can detect targets accurately under low SNR conditions.