Multi-sensor management for passive target tracking in an anti-submarine warfare scenario

1999 ◽  
Author(s):  
D.E. Penny
Keyword(s):  
Target Tracking ◽  
Sensor Management ◽  
Passive Target Tracking

Shifted Rayleigh filter: a novel estimation filtering algorithm for pervasive underwater passive target tracking for computation in 3D by bearing and elevation measurements

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lakshmi M. Kavitha ◽  
Rao S. Koteswara ◽  
K. Subrahmanyam
Keyword(s):  
Target Tracking ◽  
Long Range ◽  
Target Location ◽  
Unscented Kalman Filter ◽  
Three Dimensional ◽  
Content Type ◽  
Solution Convergence ◽  
Passive Target Tracking ◽  
Underwater Target ◽  
Target Motion Analysis

Purpose Marine exploration is becoming an important element of pervasive computing underwater target tracking. Many pervasive techniques are found in current literature, but only scant research has been conducted on their effectiveness in target tracking. Design/methodology/approach This research paper, introduces a Shifted Rayleigh Filter (SHRF) for three-dimensional (3 D) underwater target tracking. A comparison is drawn between the SHRF and previously proven method Unscented Kalman Filter (UKF). Findings SHRF is especially suitable for long-range scenarios to track a target with less solution convergence compared to UKF. In this analysis, the problem of determining the target location and speed from noise corrupted measurements of bearing, elevation by a single moving target is considered. SHRF is generated and its performance is evaluated for the target motion analysis approach. Originality/value The proposed filter performs better than UKF, especially for long-range scenarios. Experimental results from Monte Carlo are provided using MATLAB and the enhancements achieved by the SHRF techniques are evident.

Bayesian Localized Energy Optimized Sensor Distribution for Efficient Target Tracking

2019 ◽  
pp. 1-14
Author(s):  
Alonshia S. Elayaraja
Keyword(s):  
Target Tracking ◽  
Sensor Node ◽  
Management Strategies ◽  
Extended Period ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sensor Management ◽  
Node Localization ◽  
Time Optimal ◽  
Energy Consumption Rate

Many applications in wireless sensor networks perform localization of nodes over an extended period of time. Optimal selection algorithm poses new challenges to the overall transmission power levels for target detection, and thus, localized energy optimized sensor management strategies are necessary for improving the accuracy of target tracking. In this chapter, a proposal plan to develop a Bayesian localized energy optimized sensor distribution scheme for efficient target tracking in wireless sensor network is designed. The sensor node localization is done with Bayesian average, which estimates the sensor node's energy optimality. Then the sensor nodes are localized and distributed based on the Bayesian energy estimate for efficient target tracking. The sensor node distributional strategy improves the accuracy of identifying the targets to be tracked quickly. The performance is evaluated with parameters such as accuracy of target tracking, energy consumption rate, localized node density, and time for target tracking.

Game theoretic sensor management for target tracking

2010 ◽  
Author(s):  
Dan Shen ◽  
Genshe Chen ◽  
Erik Blasch ◽  
Khanh Pham ◽  
Philip Douville ◽  
...  
Keyword(s):  
Target Tracking ◽  
Sensor Management ◽  
Game Theoretic
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