基于多级恒模阵的拖线阵拖转时的阵形自校准方法

Turning towed array shape self-calibration via multistage constant modulus array

针对拖船转弯时,弯曲的拖曳线列阵的波束形成和方位估计,提出了一种先盲捕获信号,再校准阵形并估计目标方位的方法。该方法首先利用多级恒模阵对多个独立的目标信号进行盲分离,并估计出拖线阵对目标的方向向量;然后再根据方向向量对拖线阵阵形进行校准并估计出目标方位。其中,阵形自校准时的核心问题——一个多维非线性约束最小二乘问题采用了遗传算法进行求解。文中还推导了对阵元位置和目标方位估计的克拉美罗界。针对较大弯曲度拖线阵的计算机仿真实验,结果表明该方法不依赖于阵形就可实现对目标信号的捕获与分离,具有自适应抑制其它方向入射干扰信号的能力,并可以对阵形和目标方位进行有效估计。仿真结果验证了方法的正确性和有效性。

When the tow vessel was turned, beamforming and the Directions-of-Arrival （DOA） estimation would be critically degraded if the horizontal towed linear array shape was still assumed to be a straight line. In this paper, an effective method was proposed to self-callbrate the bended towed array shape based on the blind signal separation, which could simultaneously estimate the DOAs and the sensor locations. Firstly, the arbitrary number of incident independent signals and their corresponding steering vectors were blindly recovered from the output of the multistage Constant Modulus （CM） array without any information of the towed array shape. Then, based on the estimated steering vectors, the array shape self-calibration problem could be described as a nonlinear constrained least-squares problem and solved by the Genetic Algorithm. Finally, the Cramér-Rao Bounds （CRB） for the estimation was derived and computer simulations were conducted. It was shown that the signal reconstruction ability was not affected by the towed array shape deformation magnitude and the interference could be adaptively restrained by using the multistage CM array. Results from the simulations verified that the proposed method can not only blindly recover the incident signals, but also effectively estimate the DOAs and the bended towed array shape.