适用于事件触发的分布式随机目标跟踪方法

发布时间：2018-03-12 15:14

本文选题：事件触发　切入点：RSSI　出处：《自动化学报》2017年08期 　论文类型：期刊论文

【摘要】：研究了一类基于RSSI(Received signal strength indication)测距的分布式移动目标跟踪问题,提出了一种适用于事件触发无线传感器网络(Wireless sensor networks,WSNs)的分布式随机目标跟踪方法.首先考虑移动机器人模型的不确定性,引入了带有随机参数的过程噪声协方差,应用改进平方根容积卡尔曼滤波(Square root cubature Kalman filter,SRCKF)得到局部估计;然后采用无模型CI(Covariance intersection)融合估计方法以降低随机过程噪声协方差带来的不利影响.该方法充分利用有模型和无模型方法的优势,实现系统模型和量测不理想情况下的分布式目标跟踪.基于E-puck机器人的目标跟踪实验表明,事件触发的工作模式可有效地减少能量消耗,带随机参数的滤波方法更适合于随机目标的跟踪.
[Abstract]:Study a class based on RSSI (Received signal strength indication) distributed mobile target tracking, proposes a wireless sensor network for triggering events (Wireless sensor, networks, WSNs) randomly distributed target tracking method. Firstly, considering the uncertainty of the model of mobile robot is introduced, the process noise covariance with random parameters. Application of improved square root volume filter (Square root cubature Kalman Calman filter, SRCKF) to obtain the local estimation; then the model of CI (Covariance intersection) fusion estimation method to reduce the adverse effects brought by the random process noise covariance. The method makes full use of the model and model free methods advantages, realize the system model and the measurement is not ideal distributed target tracking under the E-puck. The experiments show that the robot target tracking based on event trigger The working mode can effectively reduce the energy consumption, and the filtering method with random parameters is more suitable for the tracking of random targets.

【作者单位】：浙江工业大学信息工程学院;浙江省嵌入式系统联合重点实验室;
【基金】：国家自然科学基金(61273117,61673351,61573319) 浙江省自然科学基金(LR16F030005,LZ15F030003)资助~~
【分类号】：TN929.5;TP212.9;TP242

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