基于声图像的运动目标检测与跟踪交互算法

Bingqing Li, Guanghui Ren, Zhongshu Pan, Tingting Teng
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引用次数: 1

摘要

运动目标的检测与跟踪作为检测与跟踪系统的一项关键技术,受到了广泛的关注。为了达到跟踪目标的目的,传统方法必须先完成对目标的检测,然后再对目标进行跟踪。然而,这类方法需要采用恒虚警率的方法对接收到的整帧图像进行检测,不仅降低了检测效率,而且降低了目标跟踪的性能。为了在水下强噪声和杂波干扰条件下实现对潜水员等小型运动目标的实时监控,提出了一种基于声图像的运动目标检测与跟踪交互式算法,并对目标检测系统和目标跟踪系统进行了综合分析。在目标跟踪单元中,交互式算法利用数据互连来去除目标检测产生的假目标;外推目标的轨迹,并利用卡尔曼滤波预测下一时刻目标可能出现的位置。这些消息将在检测单元中用作先验信息。在检测单元中,首先建立一个门,门的中心为目标跟踪单元预测的位置。对于下一时刻接收到的图像,采用恒虚警率的方法在预测门中进行检测,然后将检测结果反馈给跟踪单元。与现有方法相比,该算法能有效提高目标检测效率和跟踪性能,为水下小目标的监测提供了更好的途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Moving target detection and tracking interactive algorithm based on acoustic image
As a key technology of detection and tracking system, moving target detection and tracking has attracted a great deal of attention. To achieve the goal of tracking target, conventional methods have to complete the detection of targets firstly, and then track the target. However, such kind of approaches require using the method of constant false-alarm rate to detect the whole frame image received at that time, which not only reduces the detection efficiency but also degrades the performance of target tracking. In order to implement real-time monitoring divers and other small moving targets under the conditions of strong underwater noise and clutter interference, an interactive algorithm for moving target detection and tracking is proposed based on acoustic image, which jointly analyzes the target detection system and the target tracking system. In the target tracking unit, the interactive algorithm takes advantage of data interconnection to remove the false targets produced by target detection; extrapolates the target's track, and predicts the location that the target may appear at the next moment by employing the Kalman filter. These messages will be used as priori information in the detection unit. In the detection unit, first of all, a gate is established whose center is the position that the target tracking unit predicted. For the image received at the next moment, detection in the predicted gate in implemented by using the method of constant false-alarm rate, followed by feeding back the detection results to the tracking unit. Compared with existed methods, the proposed algorithm can effectively improve the target detection efficiency and tracking performance, providing a better approach to monitor underwater small targets.
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