Aspects of detection and tracking of ground targets from an airborne EO/IR sensor

Bhashyam Balaji; Rajiv Sithiravel; Zahir Daya; Thiagalingam Kirubarajan

doi:10.1117/12.2179283

21 May 2015 Aspects of detection and tracking of ground targets from an airborne EO/IR sensor

Bhashyam Balaji, Rajiv Sithiravel, Zahir Daya, Thiagalingam Kirubarajan

Proceedings Volume 9474, Signal Processing, Sensor/Information Fusion, and Target Recognition XXIV; 947403 (2015) https://doi.org/10.1117/12.2179283
Event: SPIE Defense + Security, 2015, Baltimore, MD, United States

Abstract

An airborne EO/IR (electro-optical/infrared) camera system comprises of a suite of sensors, such as a narrow and wide field of view (FOV) EO and mid-wave IR sensors. EO/IR camera systems are regularly employed on military and search and rescue aircrafts. The EO/IR system can be used to detect and identify objects rapidly in daylight and at night, often with superior performance in challenging conditions such as fog. There exist several algorithms for detecting potential targets in the bearing elevation grid. The nonlinear filtering problem is one of estimation of the kinematic parameters from bearing and elevation measurements from a moving platform. In this paper, we developed a complete model for the state of a target as detected by an airborne EO/IR system and simulated a typical scenario with single target with 1 or 2 airborne sensors. We have demonstrated the ability to track the target with `high precision' and noted the improvement from using two sensors on a single platform or on separate platforms. The performance of the Extended Kalman filter (EKF) is investigated on simulated data. Image/video data collected from an IR sensor on an airborne platform are processed using an image tracking by detection algorithm.

Citation Download Citation

Bhashyam Balaji, Rajiv Sithiravel, Zahir Daya, and Thiagalingam Kirubarajan "Aspects of detection and tracking of ground targets from an airborne EO/IR sensor", Proc. SPIE 9474, Signal Processing, Sensor/Information Fusion, and Target Recognition XXIV, 947403 (21 May 2015); https://doi.org/10.1117/12.2179283

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