Data Association Method for Radar Network Based on Time Restraint

Data association is one of the most important issues in multi-target tracking for radar network. In order to meet the high real-time requirement of the multi-target tracking system in the future, a data association method based on time restraint is presented. Firstly, the modified association probability matrix between the observations and tracks is calculated, and the optimal association model is established. Then, the time restraint based auction algorithm is proposed to solve the association issue. The design and flow of this algorithm is offered, and the simulation of the method is designed. Simulation results demonstrate that the proposed method has an ideal association performance in the restrained time.

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An Improved Probabilistic Data Association Method for Multi-Target Tracking in Clutter

Electrical, Information Engineering and Mechatronics 2011 - Lecture Notes in Electrical Engineering ◽

10.1007/978-1-4471-2467-2_164 ◽

2012 ◽

pp. 1375-1382

Author(s):

Yazhao Wang ◽

Yingmin Jia ◽

Junping Du ◽

Fashan Yu

Keyword(s):

Target Tracking ◽

Data Association ◽

Probabilistic Data ◽

Probabilistic Data Association ◽

Multi Target Tracking ◽

Association Method

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Linear Multi-Target Integrated Probabilistic Data Association Filter With Automatic Track Management for Autonomous Vehicles

Volume 2: Control and Optimization of Connected and Automated Ground Vehicles; Dynamic Systems and Control Education; Dynamics and Control of Renewable Energy Systems; Energy Harvesting; Energy Systems; Estimation and Identification; Intelligent Transportation and Vehicles; Manufacturing; Mechatronics; Modeling and Control of IC Engines and Aftertreatment Systems; Modeling and Control of IC Engines and Powertrain Systems; Modeling and Management of Power Systems ◽

10.1115/dscc2018-8930 ◽

2018 ◽

Author(s):

Andinet Hunde ◽

Beshah Ayalew

Keyword(s):

Target Tracking ◽

Tracking System ◽

Data Association ◽

Tracking Algorithm ◽

Probabilistic Data ◽

Probabilistic Data Association ◽

Address Data ◽

Multi Target Tracking ◽

Track Management ◽

Track Initiation

Target tracking in public traffic calls for a tracking system with automated track initiation and termination facilities in a randomly evolving driving environment. In addition, the key problem of data association needs to be handled effectively considering the limitations in the computational resources onboard an autonomous car. In this paper, we discuss a multi-target tracking system that addresses target birth/initiation and death/termination processes with automatic track management feature. The tracking system is based on Linear Multi-target Integrated Probabilistic Data Association Filter (LMIPDAF), which is adapted to specifically include algorithms that handle track initiation and termination, clutter density estimation and track management. The performance of the proposed tracking algorithm is compared to other single and multi-target tracking schemes and is shown to have acceptable tracking error. It is further illustrated through multiple traffic simulations that the computational requirement of the tracking algorithm is less than that of optimal multi-target tracking algorithms that explicitly address data association uncertainties.

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Data association method based on scenario analysis using weak tracking data for multi-target tracking

2017 International Conference on Machine Learning and Cybernetics (ICMLC) ◽

10.1109/icmlc.2017.8108986 ◽

2017 ◽

Author(s):

Zhihong Duan ◽

Patrick P.K. Chen ◽

Qianqian Wu ◽

Xian Hu

Keyword(s):

Target Tracking ◽

Scenario Analysis ◽

Data Association ◽

Tracking Data ◽

Multi Target Tracking ◽

Association Method

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Centralized Fuzzy Data Association Algorithm of Three-sensor Multi-target Tracking System

Research Journal of Applied Sciences Engineering and Technology ◽

10.19026/rjaset.7.389 ◽

2014 ◽

Vol 7 (6) ◽

pp. 1255-1260

Author(s):

Zhaofeng Su ◽

Zhenzhen Yuan ◽

Li Zhou

Keyword(s):

Target Tracking ◽

Tracking System ◽

Data Association ◽

Fuzzy Data ◽

Multi Target Tracking ◽

Association Algorithm

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An Adaptive Clustering and Inter-Cluster Negotiation Protocol for Multi-Target Tracking Based on WSN

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.457-458.1083 ◽

2012 ◽

Vol 457-458 ◽

pp. 1083-1088

Author(s):

Zhen Hua Luo ◽

Jing Zhi Ye ◽

Wen Feng Luo

Keyword(s):

Target Tracking ◽

Real Time ◽

Tracking System ◽

Base Station ◽

Sensor Nodes ◽

Wireless Sensor ◽

Data Synchronization ◽

Adaptive Clustering ◽

Multi Target Tracking ◽

Real Time Tracking

In many wireless sensor networks (WSNs), target tracking is an essential application. This paper studies the real-time target tracking algorithm and the implementation for a multi-target real-time tracking system. The system consists of a wireless sensor network which includes several distributed ultrasonic sensor nodes and a monitoring base station, and two robots as moving targets. To avoid the conflicts in the network, a sensor node task scheduling scheme, and an adaptive clustering and inter-cluster negotiation network protocol (ACICN) are proposed for the system. To cope with distributed and asynchronous measurements, data synchronization and Extended Kalman Filter (EKF) location algorithm are studied for the system. The experiments show that the system can effectively track multi targets simultaneously.

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