作者：张虎龙

作者单位：中国飞行试验研究院, 陕西 西安 710089

关键词：数据融合;传感器网络;强跟踪滤波;乘性噪声

摘要：

为解决加性噪声模型无法准确刻画实际观测模型的问题，采用带有乘性噪声系统模型进行建模。在实际系统中，由于多传感器网络的应用使得传统乘性噪声的滤波算法已无法满足实际需求，该文分别提出带有乘性噪声的有反馈分布式和序贯式多传感器强跟踪滤波融合方法，以有效解决复杂环境下的非线性系统最优状态估计问题。计算机仿真实验表明，新算法具有很好的估计精度，在多传感器目标跟踪应用中有较好的应用前景。

Multi-sensors STF algorithms with multiplicative noise

ZHANG Hulong

Chinese Flight Test Establishment, Xi'an 710089, China

Abstract: In this paper, a multiplicative noise model is established to solve the problem that additive noise model cannot precisely describe the observed model. In actual systems, the filter algorithm of traditional multiplicative noise can no longer meet actual requirements owing to the application of multi-sensor network. Therefore, this paper puts forward respectively distributed and sequential multi-sensor strong tracking filter(STF) data fusion methods with multiplicative noise and feedback, in order to solve the optimal state estimation of nonlinear system in complex environment. Computer simulation experiments show that the new algorithm has good estimation accuracy, indicating a promising future application of multi-sensor target tracking.

Keywords: data fusion;sensor network;strong tracking filter;multiplicative noise

2017, 43(5): 101-104  收稿日期: 2016-11-18;收到修改稿日期: 2016-12-24

基金项目: 航空科学基金（2015ZD30002）

作者简介: 张虎龙(1979-),男,湖南岳阳市人,高级工程师,研究方向为飞行试验光电测试技术。

参考文献

[1] KALMAN R E. A new approach to linear filtering and prediction problems[J]. Journal of Basic Engineering,1960, 82(1):35-45.
[2] 付梦印,邓志红. Kalman滤波理论及其在导航系统中的应用[M]. 北京:科学出版社,2003:40-42.
[3] 文成林. 多尺度动态建模理论及其应用[M]. 北京:科学出版社,2007:76-79.
[4] 褚东升,宁云磊,张玲. 带乘性噪声系统状态滤波的自适应算法[J]. 中国海洋大学学报(自然科学版),2011,41(12):109-113.
[5] 张玲,王蕊,褚东升. 基于复杂多通道带乘性噪声模型的水声通信字符估计算法[J]. 中国海洋大学学报(自然科学版),2015,45(1):110-113.
[6] 王昌盛,张玲,臧爱云,等. 带乘性噪声附等式约束的非线性系统滤波算法[J]. 中国海洋大学学报(自然科学版),2016,46(8):137-140.
[7] SONG Y, WANG B, SHI Z J, et al. Distributed algorithms for energy-efficient even self-deployment in mobile sensor networks[J]. IEEE Transactions on Mobile Computing,2014,13(5):1035-1047.
[8] XU Y F, CHOI J G, OH S H. Mobile sensor network navigation using Gaussian processes with truncated observations[J]. IEEE Transactions on Robotics,2011,27(6):1118-1131.
[9] YANG C B. Kalman filtering with nonlinear state constraints[J]. IEEE Transactions on Aerospace and Electronic Systems,2009,45(1):70-84.
[10] 李超. 基于非线性滤波的飞行器姿态确定算法研究[D]. 杭州:杭州电子科技大学,2011.