In complex underwater environments,the issues of high-robustness estimation and Direction of Arrival(DOA)tracking of underwater target bearings are addressed through adaptive beamforming and nonlinear filtering techniques.An adaptive tracking window for potential target bearings is constructed in real time,and nonlinear real-time tracking iterative feedback is provided,enabling high-robustness estimation and tracking of underwater targets to be achieved.Initially,measurements of the target′s radiated noise in the element domain are acquired using a uniform linear sonar array,and a typical kinematic model for underwater moving targets is established.Subsequently,the element domain observations at the predicted target bearing undergo spatial filtering using the Minimum Variance Distortionless Response(MVDR)beamforming technique,thus enhancing the signal-to-noise ratio of the target signal.Further,high-robustness tracking of the target bearing is conducted through the Extended Kalman Filter(EKF)technique,yielding the potential target bearing and errors.These are then fed back to the MVDR for adaptive tracking window adjustment,culminating in the high-robustness underwater target DOA tracking.Finally,multiple Monte Carlo simulation experiments indicate that under low signal-to-noise ratio conditions,when traditional DOA tracking methods and filtering tracking algorithms utilizing only element domain measurements perform poorly or fail,the proposed algorithm still maintains an average estimation error below 0.6°,demonstrating high accuracy and stability.Thus,the robustness of the proposed algorithm is proven.
关键词
波达角估计/自适应波束形成/卡尔曼滤波/方位跟踪/阵列信号处理/非线性贝叶斯滤波
Key words
Direction of Arrival Estimation/Adaptive Beamforming/Kalman Filtering/Azimuth Tracking/Array Signal Processing/Nonlinear Bayesian Filtering
维普
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