Abstract
We present an algorithm for detecting and tracking underwater mobile objects using active acoustic transmission of broadband chirp signals whose reflections are received by a hydrophone array. The method overcomes the problem of high false alarm rate by applying a track-before-detect ap- proach to the sequence of received reflections. A 2D time- space matrix is created for the reverberations received from each transmitted probe signal by performing delay and sum beamforming and pulse compression. The result is filtered by a 2D constant false alarm rate (CFAR) detector to identify reflection patterns corresponding to potential targets. Closely spaced signals for multiple probe transmissions are combined into blobs to avoid multiple detections of a single object. A track- before-detect method using a Nearly Constant Velocity (NCV) model is employed to track multiple objects. The position and velocity is estimated by the debiased converted measurement Kalman filter. Results are analyzed for simulated scenarios and for experiments at sea, where GPS tagged gilt-head seabream fish were tracked. Compared to two benchmark schemes, the results show a favorable track continuity and accuracy that is robust to the choice of detection threshold.
Abstract (translated)
我们提出了一种使用宽带脉冲信号的主动声发射来检测和跟踪水下移动目标的算法。该方法通过应用跟踪在检测前的序列来降低虚假警报率。通过进行延迟和求和 beamforming 和脉冲压缩，为每个传输的探测信号创建了2D 时间-空间矩阵。结果通过2D 常数虚假警报率（CFAR）检测器进行滤波，以识别潜在目标的反射模式。 对于多个探测信号，将近距离的信号合并成团以避免对单个目标的多次检测。采用Nearly Constant Velocity（NCV）模型采用跟踪在检测前的方法来跟踪多个目标。通过无偏转换测量 Kalman 滤波器估计位置和速度。 在模拟场景和海上实验中分析结果。与两个基准方案相比，结果表明，该方法具有更好的跟踪连续性和准确性，并且对检测阈值的選擇具有鲁棒性。
URL
https://arxiv.org/abs/2404.10316
