Constrained Least Square Estimation Algorithm for Multisensor Bearings-Only Passive Target Tracking

Zhi Wu Xuan; Kai Nie

doi:10.4028/www.scientific.net/AMM.602-605.1842

Paper Titles

Primary Establishment of LAMP Method for Cyprinid Herpesvirus 2 Detection
p.1823

Design and Implementation of a Portable Pulse Wave Velocity Measuring Prototype
p.1829

Character Recognition Based on Wavelet Neural Network Optimized with PSO Algorithm
p.1834

The Design of Three-Dimensional Computer Room Monitoring System Based on Unity3D
p.1838

Constrained Least Square Estimation Algorithm for Multisensor Bearings-Only Passive Target Tracking
p.1842

Accuracy Analysis of Highly Kinematical Positioning of GPS
p.1847

Application of SVD-TLS Based Parameter Estimation Method in Aircraft Structural Modal Parameter Identification
p.1851

Targets Detection Based on Time Reversal Operator with Uniform Circular Array
p.1855

Research on a New Radar Antenna Pattern Measurement Method
p.1859

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 602-605Constrained Least Square Estimation Algorithm for...

Constrained Least Square Estimation Algorithm for Multisensor Bearings-Only Passive Target Tracking

Abstract:

The sensor needs to maneuver to get better observability in Bearings-Only passive target tracking with single sensor which makes the observation time longer. Multisensor Bearings-Only passive target tracking can solve the problem using exchange data. So the constrained Least Square Estimation (CLSE) algorithm is proposed for Multisensor Bearings-Only passive target tracking. The constrained condition is introduced to the Least Square Estimation algorithm firstly. Then the eigenvector corresponding to the least eigenvalue of the matrix is used to overcome the shortcoming of Extend Kalman Filter algorithm which needs the initial value. Also the bias problem of Least Square Estimation is conquered. The simulation results show that the CLSE can gradually approach the Cramer-Rao Lower Bound and its precision is better than the Least Square Estimation algorithm. Finally the CLSE is proved to be a gradually, stable and almost unbiased estimation algorithm.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 602-605)

Pages:

1842-1846

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.602-605.1842

Citation:

Cite this paper

Online since:

August 2014

Authors:

Zhi Wu Xuan*, Kai Nie

Keywords:

Constrained Least Square Algorithm, Multisensor, Passive Target Tracking, Unbiased Estimation

Export:

RIS, BibTeX

Price:

Permissions:

Request Permissions

* - Corresponding Author

References

[1] Benon P B, Jauffert C. TMA form bearings and multipath time delays[J]. IEEE Transaction on AES, 1997, 33(3): 813-824.

DOI: 10.1109/7.599251

Google Scholar

[2] Liu J, Liu Z, Xuan Z L. Study on two cooperative observes TMA algorithm[J]. Warship Science and Technology, 2006, 28(1): 64-69.

Google Scholar

[3] Guan X, He Y, Yi X. Performance simulation and analysis for double arrays Bearings-Only passive target tracking under water[J]. Journal of System Simulation, 2003, 15(10): 1464-1491.

Google Scholar

[4] Rao S K. Pseudo-linear estimator for Bearings-Only passive target tracking[J]. IEE Proc. Radar, Sonar Navigation, 2001, 148(1): 16-22.

DOI: 10.1049/ip-rsn:20010144

Google Scholar

[5] Vlieger J H, Gmelig Meyling. Maximum Likelihood Estimation for long-range target tracking using passive sonar measurements [J]. Transactions on Signal Processing, 1992, 40(5): 1216-1224.

DOI: 10.1109/78.134483

Google Scholar

[6] Van der Merwe R, Wan E A R. The square-root Unscented Kalman Filter for state and parameter estimation[C]. International Conferrence on Acoustics, Speech, and Signal Processing 2001, Salt Lake City, Utah, (2001).

DOI: 10.1109/icassp.2001.940586

Google Scholar

[7] Liu Z, Deng J L. Multisensor Bearings-Only passive target tracking and observability analysis [J]. Fire Command and Control, 2004, 29(5): 79-87.

Google Scholar

[8] Tltis R A, Anderson K L. A consistent estimation criterion for multisensor Bearings-Only with tracking [J]. IEEE Transactions on AES, 2011, 47(1): 108-121.

Google Scholar