Measure of Nonlinearity With Application to Bearings-Only Target Tracking

2021 ◽  
Vol 17 (3) ◽  
pp. 46-61
Author(s):  
Kausar Jahan ◽  
Sanagapallea Koteswara Rao
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Target Tracking ◽  
Covariance Matrices ◽  
The State ◽  
Target Motion ◽  
Underwater Environment ◽  
Passive Target Tracking ◽  
Motion Parameters

Using the recently proposed measure of nonlinearity (MoN), the authors try to find the magnitude of nonlinearity for passive target tracking with bearings-only measurements in underwater environment. The method derived to measure the nonlinearity is completely based on the state covariance matrices of the filters. It is tried to find the allowable magnitude of nonlinearity in terms of MoN with which a filter can perform to estimate the target motion parameters with required accuracy. In this paper, MoN values for different filters are computed for different scenarios. Results obtained in the Monte Carlo simulation are presented.

scholarly journals Passive Target Tracking using Unscented Kalman Filter based on Monte Carlo Simulation

2015 ◽  
Vol 8 (29) ◽  
Author(s):  
K. Lova Raju ◽  
S. Koteswara Rao ◽  
Rudra Pratap Das ◽  
M. Nalini Santhosh ◽  
A. Sampath Dakshina Murthy
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Kalman Filter ◽  
Target Tracking ◽  
Unscented Kalman Filter ◽  
Passive Target Tracking

Target tracking using Monte Carlo simulation

1998 ◽  
Vol 47 (2-5) ◽  
pp. 441-447 ◽  
Author(s):  
Tz.A. Semerdjiev ◽  
V.P. Jilkov ◽  
D.S. Angelova
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Target Tracking

Chain length dependence of the state diagram of a single stiff-chain macromolecule: Theory and Monte Carlo simulation

2003 ◽  
Vol 118 (7) ◽  
pp. 3392-3400 ◽  
Author(s):  
M. R. Stukan ◽  
V. A. Ivanov ◽  
A. Yu. Grosberg ◽  
W. Paul ◽  
K. Binder
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Chain Length ◽  
State Diagram ◽  
The State ◽  
Length Dependence ◽  
Stiff Chain

scholarly journals State of Charge Dependent Ordered and Disordered Phases in a Li[Ni1/3Co1/3Mn1/3]O2 Cathode Material

2021 ◽  
Author(s):  
Chi Ho Lee ◽  
Byeongsun Jun ◽  
Seung Cheol Lee ◽  
Sang Uck Lee
Keyword(s):  
Phase Transition ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Cathode Material ◽  
Structural Phase Transition ◽  
Cluster Expansion ◽  
Density Functional ◽  
Structural Phase ◽  
The State ◽  
State Of Charge

We systematically investigated the structural phase transition of Li[Ni1/3Co1/3Mn1/3]O2 (NCM) cathode material depending on the state of charge (SOC) using cluster expansion Monte Carlo simulation (CE-MCS) combined with density functional...

Pervasive underwater passive target tracking for the computation of standard deviation solution in a 3D environment

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
M. Kavitha Lakshmi ◽  
S. Koteswara Rao ◽  
Kodukula Subrahmanyam
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Kalman Filter ◽  
Standard Deviation ◽  
Target Tracking ◽  
Unscented Kalman Filter ◽  
Three Dimensional ◽  
Content Type ◽  
3D Space ◽  
Underwater Target

PurposeNowadays advancement in acoustic technology can be explored with marine assets. The purpose of the paper is pervasive computing underwater target tracking has aroused military and civilian interest as a key component of ocean exploration. While many pervasive techniques are currently found in the literature, there is little published research on the effectiveness of these paradigms in the target tracking context.Design/methodology/approachThe unscented Kalman filter (UKF) provides good results for bearing and elevation angles only tracking. Detailed methodology and mathematical modeling are carried out and used to analyze the performance of the filter based on the Monte Carlo simulation.FindingsDue to the intricacy of maritime surroundings, tracking underwater targets using acoustic signals, without knowing the range parameter is difficult. The intention is to find out the solution in terms of standard deviation in a three-dimensional (3D) space.Originality/valueA new method is found for the acceptance criteria for range, course, speed and pitch based on the standard deviation for bearing and elevation 3D target tracking using the unscented Kalman filter covariance matrix. In the Monte Carlo simulation, several scenarios are used and the results are shown.

An Engineering Approach for Observer Trajectory Optimization in Passive Target Tracking System

2014 ◽  
Vol 556-562 ◽  
pp. 3223-3226 ◽  
Author(s):  
Chong Zhao ◽  
Hong Wei Quan ◽  
Dong Liang Peng
Keyword(s):  
Monte Carlo ◽  
Target Tracking ◽  
General Principle ◽  
Surveillance System ◽  
Trajectory Optimization ◽  
Tracking System ◽  
Target Localization ◽  
Engineering Approach ◽  
Passive Target Tracking ◽  
Localization And Tracking

In passive target tracking system, the observer trajectories have an important effect on the accuracy of target localization and tracking. This paper addressed an engineering approach to optimize the trajectory altitude of observer platform for airborne ESM surveillance system. The method proposed is based on Monte-Carlo run, which avoid complicated theoretical deduction and make the observer path easy-to-practice. By the analysis, the general principle of observer trajectory altitude optimization can be obtained. Within the range of allowed flying altitudes for observer, the measurements of elevation should be maintain or close to 45 degrees as much as possible.

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