拖曳阵被动合成孔径目标深度稳健估计

使用水下无人平台作为载体的拖曳阵进行被动目标深度估计具有灵活性高和隐蔽性好的优点,针对实际应用中存在的平台自噪声和阵列瞬时随机加速度扰动问题,提出了一种稳健的目标深度估计方法。该方法分为三个步骤,首先对阵元接收信号进行自适应噪声抵消和相位抖动滤波,然后对声压进行距离积分实现简正波模态估计,最后计算模态匹配度,最大值对应的深度为目标深度估计结果。仿真表明在干扰背景下该方法的目标深度估计稳健性优于传统方法,声源频率、合成孔径距离和信干比决定了目标深度估计误差。利用实验数据验证了该方法对水下低频线谱声源的深度估计能力。

Robust estimation of target depth for towed array using synthetic aperture algorithm

The use of a towed array with an underwater unmanned vehicle as the carrier for target depth estimation has the advantages of high flexibility and prominent concealment. Aiming at the problems of UUV self-noise and random instantaneous acceleration interference in practical applications, a robust method for towed array using synthetic aperture algorithm is proposed. The method is divided into three steps. First, adaptive noise cancellation and phase jitter filtering are performed on the received signals of the array sensors. Then, the sound pressure is subjected to distance integration to estimate the normal mode distribution. Finally, the matched-mode degree is calculated, and the depth corresponding to the maximum value is the target depth estimation. Simulations show that the robustness of the modal depth estimation of the sound field integration method is better than that of traditional methods. The source frequency, synthetic aperture distance, and signal-to-interference ratio determine the target depth estimation error. The estimation of underwater low frequency tonal source is experimentally verified