Autonomous Bayesian Search and Tracking, and its Experimental Validation
Autonomous Bayesian Search and Tracking, and its Experimental Validation
复制标题
自主贝叶斯搜索和跟踪及其实验验证
DOI：
10.1163/156855311x617461
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发表时间：
2012
影响因子：
2
通讯作者：
R. Madhavan
中科院分区：
文献类型：
--
作者：
T. Furukawa;L. C. Mak;H. Durrant;R. Madhavan
我们提出了一种技术，该技术统一控制一个自主传感器平台团队，该团队负责在递归贝叶斯估计框架内搜索和跟踪移动目标的双重任务。该方法定义了目标可检测区域，并统一表述了具有检测事件和无检测事件的观测似然。统一似然函数允许该技术在不考虑目标可检测性的情况下更新和维护目标信念。对于统一搜索和跟踪（SAT），该技术进一步在有限时间范围内预测信念，并通过由预测信念导出的局部和全局度量组成的统一目标函数最大化来决定控制动作。利用目标函数，该方法可以平滑地改变其控制动作，即使在SAT之间的转换。数值结果首先表明，该方法在不同检测能力的传感器平台上进行了测试，并在不同先验知识下与传统搜索技术进行了比较。最后，通过协调的SAT现场实验验证了该技术的适用性和可扩展性。
We present a technique that uniformly controls a team of autonomous sensor platforms charged with the dual task of searching for and then tracking a moving target within a recursive Bayesian estimation framework. The proposed technique defines the target detectable region, and uniformly formulates observation likelihoods with detection and no-detection events. The unified likelihood function allows the proposed technique to update and maintain the target belief, regardless of the target detectability. For unified search and tracking (SAT), the proposed technique further predicts the belief in a finite-time horizon, and decides control actions by maximizing a unified objective function consisting of local and global measures derived from the predicted belief. Using the objective function, the proposed technique can smoothly change its control actions even during transitions between SAT. The numerical results first show successful SAT by the proposed technique in tests using a sensor platform with different detectability and comparison with conventional searching techniques under different prior knowledge, and then identifies the superiorities of the proposed technique in SAT. The experimental results finally validate the applicability and extendability of the proposed technique via coordinated SAT in a field experiment.