Precision targeting in guided munition using IR sensor and MmW radar

S. Sreeja; H. B. Hablani; H. Arya

doi:10.1117/12.2194488

21 October 2015 Precision targeting in guided munition using IR sensor and MmW radar

S. Sreeja, H. B. Hablani, H. Arya

Proceedings Volume 9653, Target and Background Signatures; 96530M (2015) https://doi.org/10.1117/12.2194488
Event: SPIE Security + Defence, 2015, Toulouse, France

Abstract

Conventional munitions are not guided with sensors and therefore miss the target, particularly if the target is mobile. The miss distance of these munitions can be decreased by incorporating sensors to detect the target and guide the munition during flight. This paper is concerned with a Precision Guided Munition(PGM) equipped with an infrared sensor and a millimeter wave radar [IR and MmW, for short]. Three-dimensional flight of the munition and its pitch and yaw motion models are developed and simulated. The forward and lateral motion of a target tank on the ground is modeled as two independent second-order Gauss-Markov process. To estimate the target location on the ground and the line-of-sight rate to intercept it an Extended Kalman Filter is composed whose state vector consists of cascaded state vectors of missile dynamics and target dynamics. The line-of-sight angle measurement from the infrared seeker is by centroiding the target image in 40 Hz. The centroid estimation of the images in the focal plane is at a frequency of 10 Hz. Every 10 Hz, centroids of four consecutive images are averaged, yielding a time-averaged centroid, implying some measurement delay. The miss distance achieved by including by image processing delays is 1:45m.

Citation Download Citation

S. Sreeja, H. B. Hablani, and H. Arya "Precision targeting in guided munition using IR sensor and MmW radar", Proc. SPIE 9653, Target and Background Signatures, 96530M (21 October 2015); https://doi.org/10.1117/12.2194488

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KEYWORDS

Target detection

Infrared sensors

Sensors

Image processing

Extremely high frequency

Missiles

Motion models

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