A Novel Multi-Passive-Sensor Target Tracking Algorithm Based On Gaussian Filter
نویسندگان
چکیده
This paper presents a new multi-passive-sensor target tracking algorithm which yields a nonlinear state estimator called Gaussian filter based on deterministic sampling. Firstly, this state estimator employs a deterministic sample selection scheme, where a parametric density function representation of the sample points is employed to approximate the cumulative distribution function of the prior Gaussian density. The performance of the filter is more accurate than the extended Kalman Filter (EKF) and the unscented Kalman Filter (UKF) in nonlinear dynamic system. Secondly, in order to avoid the unobservability problem of passive target tracking, a nonlinear measurement model of multiple passive sensors is founded. Finally, the algorithm performance has been verified by illustrating some simulation results.
منابع مشابه
Target Tracking with Unknown Maneuvers Using Adaptive Parameter Estimation in Wireless Sensor Networks
Abstract- Tracking a target which is sensed by a collection of randomly deployed, limited-capacity, and short-ranged sensors is a tricky problem and, yet applicable to the empirical world. In this paper, this challenge has been addressed a by introducing a nested algorithm to track a maneuvering target entering the sensor field. In the proposed nested algorithm, different modules are to fulfill...
متن کاملTarget Tracking Based on Virtual Grid in Wireless Sensor Networks
One of the most important and typical application of wireless sensor networks (WSNs) is target tracking. Although target tracking, can provide benefits for large-scale WSNs and organize them into clusters but tracking a moving target in cluster-based WSNs suffers a boundary problem. The main goal of this paper was to introduce an efficient and novel mobility management protocol namely Target Tr...
متن کاملMultiple Target Tracking in Wireless Sensor Networks Based on Sensor Grouping and Hybrid Iterative-Heuristic Optimization
A novel hybrid method for tracking multiple indistinguishable maneuvering targets using a wireless sensor network is introduced in this paper. The problem of tracking the location of targets is formulated as a Maximum Likelihood Estimation. We propose a hybrid optimization method, which consists of an iterative and a heuristic search method, for finding the location of targets simultaneously. T...
متن کاملA New Modified Particle Filter With Application in Target Tracking
The particle filter (PF) is a novel technique that has sufficiently good estimation results for the nonlinear/non-Gaussian systems. However, PF is inconsistent that caused mainly by loss of particle diversity in resampling step and unknown a priori knowledge of the noise statistics. This paper introduces a new modified particle filter called adaptive unscented particle filter (AUPF) to overcome th...
متن کاملAn Efficient Target Tracking Algorithm Based on Particle Filter and Genetic Algorithm
In this paper, we propose an efficient hybrid Particle Filter (PF) algorithm for video tracking by employing a genetic algorithm to solve the sample impoverishment problem. In the presented method, the object to be tracked is selected by a rectangular window inside which a few numbers of particles are scattered. The particles’ weights are calculated based on the similarity between feature vecto...
متن کامل