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An Active Acoustic Track-Before-Detect Approach for Finding Underwater Mobile Targets

机译:一种主动声波探测前方法来寻找水下移动目标

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We consider the challenge of tracking and estimating the size of a single submerged target in a high reverberant underwater environment using a single active acoustic transceiver. This problem is common for a multitude of applications, ranging from the security and safety needs of tracking submerged vehicles and scuba divers, to environmental research and management implications such as the monitoring of pelagic fauna. Considering that the target can be either slow (e.g., a scuba diver) or fast moving (e.g., a shark), we avoid continuous signaling, and rely on the emission of widehand pulses whose reflection pattern are evaluated and reshaped in a time-distance matrix. As opposed to common approaches that track targets through template matching or by using tracking filters, we avoid making difficult assumptions about the target's reflection patterns or motion type, and instead perform probabilistic tracking using a constraint Viterbi algorithm, whereby detection is determined based on maximum likelihood criterion. In this process, we use the expectation-maximization approach to manage stationary reflections through distribution analysis, which otherwise may be misidentified as targets. Based on the tracked path, we then evaluate the target's size. To test our approach, we performed extensive simulations as well as eight sea experiments in different environmental settings to track both a scuba diver and a sandbar shark (Carcharhinus plumbeus). The simulation results show a tracking performance that is close to the Cramer-Rao lower bound, and the experiment results show a good tradeoff between detection rate and false alarm rate for a low signal-to-clutter ratio of 5 dB, and average tracking error of 1.5 and 6.5 m in the detections of a scuba diver and sandbar shark, respectively. For reproducibility, we share our sea experiment data.
机译:我们考虑了使用单个有源声波收发器在高混响水下环境中跟踪和估计单个淹没目标的尺寸的挑战。从跟踪潜水器和潜水员的安全性需求到环境研究和管理意义(例如中上层动物的监视),这个问题在许多应用中都很常见。考虑到目标可能是慢速运动(例如,潜水员)或快速运动(例如,鲨鱼),我们避免了连续信号传递,而是依靠宽阔脉冲的发射,该宽阔脉冲的反射模式经过评估并在一段时间内进行了整形矩阵。与通过模板匹配或使用跟踪过滤器跟踪目标的常见方法相反,我们避免对目标的反射模式或运动类型做出困难的假设,而是使用约束维特比算法执行概率跟踪,从而根据最大似然来确定检测标准。在此过程中,我们使用期望最大化方法通过分布分析来管理平稳反射,否则可能会将其误识别为目标。然后根据跟踪的路径评估目标的大小。为了测试我们的方法,我们在不同的环境下进行了广泛的模拟以及八次海上实验,以追踪潜水员和沙洲鲨(Carcharhinus plumbeus)。仿真结果表明跟踪性能接近Cramer-Rao下限,并且实验结果表明,对于5 dB的低信杂比,检测率与误报率之间具有良好的权衡,并且平均跟踪误差在潜水员和沙洲鲨鱼的探测中分别达到1.5 m和6.5 m。为了重现性,我们共享我们的海上实验数据。

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