A Modified Particle Filter Algorithm for Wireless Capsule Endoscope Location Tracking
نویسندگان
چکیده
Tracking a capsule endoscope location is one of promising application offered by implant body area networks (BANs). In this paper, we pay attention to a particle filter algorithm with received signal strength indicator (RSSI)-based localization in order to solve the capsule endoscope location tracking problem, which assumes a nonlinear transition model on the capsule endoscope location. However, the original particle filter requires to calculate the particle weight according to its condition (namely, its likelihood value), while the transition model on capsule endoscope location has some model parameters which cannot be estimated by received wireless signal. Therefore, for the purpose of applying the particle filter to the capsule endoscope tracking, this paper makes some modifications in the resampling step of the particle filter algorithm. Our computer simulation results demonstrates that the proposed tracking methods with the modified particle filter can improve the performance as compared with not only the conventional maximum likelihood (ML) localization but also the original particle filter-based location tracking.
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 کاملSimultaneous Estimation of WCE Moving Distance and Heading Direction Based on RSSI-based Localization
In this paper, we propose a simultaneous moving distance and heading direction estimation method for wireless capsule endoscope (WCE) system only with RSSI measurement data, which can be obtained as a fundamental function of wireless communications. This paper first focuses on an RSSI-based WCE location tracking method with a particle filter algorithm. Then, in order to accurately estimate the ...
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 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 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 کامل