Optimal band analysis for dim target detection in space-variant sky background

Xiaoyu He; Xiaojian Xu

doi:10.1117/12.2503530

9 October 2018 Optimal band analysis for dim target detection in space-variant sky background

Xiaoyu He, Xiaojian Xu

Proceedings Volume 10795, Electro-Optical and Infrared Systems: Technology and Applications XV; 107950N (2018) https://doi.org/10.1117/12.2503530
Event: SPIE Security + Defence, 2018, Berlin, Germany

Abstract

In this paper, a target and background driven simulation procedure is developed for optimal band analysis and performance evaluation of multispectral sensors for dim target detection, in which the observation geometry, target and background radiant characteristics, and the influence of infrared sensor system are integrated into. With the specified sensor altitude, the BeiHang University - Atmospheric Transfer Model (BHU-ATM) is adopted to calculate spectral irradiances of space-variant sky background. When a target with an assumed altitude exists in one line of sight (LOS), the corresponding nadir angle is used to calculate the distance between the target and the sensor, which impacts the target spectral irradiance at the sensor aperture. To analyze the optimal band for target detection, a set of spectral response functions with different central wavelengths and bandwidths are designed to calculate the target-to-background contrasts as well as the signal-to-noise ratios (SNRs). To demonstrate the usefulness of the developed procedure, typical sensor parameters are used to analyze the optimal band for aircraft detection. The band achieving the highest SNR is selected and used in the radiant image simulation for performance evaluation. The results show that the detection performance is related to spectral band as well as the LOS direction.

Citation Download Citation

Xiaoyu He and Xiaojian Xu "Optimal band analysis for dim target detection in space-variant sky background", Proc. SPIE 10795, Electro-Optical and Infrared Systems: Technology and Applications XV, 107950N (9 October 2018); https://doi.org/10.1117/12.2503530

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