State estimators for tracking sharply-maneuvering ground targets

Radu S. Visina; Yaakov Bar-Shalom; Peter Willett

doi:10.1117/12.2262386

2 May 2017 State estimators for tracking sharply-maneuvering ground targets

Radu S. Visina, Yaakov Bar-Shalom, Peter Willett

Proceedings Volume 10200, Signal Processing, Sensor/Information Fusion, and Target Recognition XXVI; 1020005 (2017) https://doi.org/10.1117/12.2262386
Event: SPIE Defense + Security, 2017, Anaheim, CA, United States

Abstract

This paper presents an algorithm, based on the Interacting Multiple Model Estimator, that can be used to track the state of kinematic point targets, moving in two dimensions, that are capable of making sharp heading maneuvers over short periods of time, such as certain ground vehicles moving in an open field. The targets are capable of up to 60 °/s turn rates, while polar measurements are received at 1 Hz. We introduce the Non-Zero Mean, White Noise Turn-Rate IMM (IMM-WNTR) that consists of 3 modes based on a White Noise Turn Rate (WNTR) kinematic model that contains additive, white, Gaussian turn rate process noises. Two of the modes are considered maneuvering modes, and they have opposite (left/right), non-zero mean turn rate input noise. The need for non-zero mean turn rate process noise is explained, and Monte Carlo simulations compare this novel design to the traditional (single-mode) White Noise Acceleration Kalman Filter (WNA KF) and the two-mode White Noise Acceleration/Nearly-Coordinated Turn Rate IMM (IMM-CT). Results show that the IMM-WNTR filter achieves better accuracy and real-time consistency between expected error and actual error as compared to the (single-mode) WNA KF and the IMM-CT in all simulated scenarios, making it a very accurate state estimator for targets with sharp coordinated turn capability in 2D.

Conference Presentation

Citation Download Citation

Radu S. Visina, Yaakov Bar-Shalom, and Peter Willett "State estimators for tracking sharply-maneuvering ground targets", Proc. SPIE 10200, Signal Processing, Sensor/Information Fusion, and Target Recognition XXVI, 1020005 (2 May 2017); https://doi.org/10.1117/12.2262386

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available