An infrared wide-area imaging simulation method

The core of infrared sensor detection is to extract targets from system noise. To evaluate the detection capability of the sensor, it is necessary to comprehensively consider factors such as orbital motion, sensor noise, sensor optical axis disturbance, and scene noise to achieve accurate calculation of system noise. The existing research mainly focuses on reshaping the background texture features and achieving image simulation through image square construction. However, there is a lack of rigorous imaging geometric models and few consideration of detection elements. This paper proposes an infrared wide area imaging simulation method, which establishes the object image relationship from orbit simulation and can achieve accurate imaging simulation in the time domain. We have completed the detection of factors such as targets, backgrounds, atmospheres, stars, clouds, etc., and can achieve the construction of complex global all-weather scene models. In terms of load imaging simulation, a sensor noise model was established using the load error transfer algorithm, and the system noise was calculated. Through comparison with in orbit measured data, it was found that the simulation accuracy of the system detection capability was better than 70%, and the geometric positioning error was less than 600m. It can effectively support the ability estimation of low and high orbit infrared detection satellites and achieve closed-loop analysis from load indicators to detection capability.

Authors

Publication Details

Published
2025-09-15
DOI
https://doi.org/10.1117/12.3073705
Primary Topic
Infrared Target Detection Methodologies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

An infrared wide-area imaging simulation method

Lu Zhijun
Infrared Target Detection Methodologies
article

An infrared wide-area imaging simulation method

Lu Zhijun
article en

Abstract

The core of infrared sensor detection is to extract targets from system noise. To evaluate the detection capability of the sensor, it is necessary to comprehensively consider factors such as orbital motion, sensor noise, sensor optical axis disturbance, and scene noise to achieve accurate calculation of system noise. The existing research mainly focuses on reshaping the background texture features and achieving image simulation through image square construction. However, there is a lack of rigorous imaging geometric models and few consideration of detection elements. This paper proposes an infrared wide area imaging simulation method, which establishes the object image relationship from orbit simulation and can achieve accurate imaging simulation in the time domain. We have completed the detection of factors such as targets, backgrounds, atmospheres, stars, clouds, etc., and can achieve the construction of complex global all-weather scene models. In terms of load imaging simulation, a sensor noise model was established using the load error transfer algorithm, and the system noise was calculated. Through comparison with in orbit measured data, it was found that the simulation accuracy of the system detection capability was better than 70%, and the geometric positioning error was less than 600m. It can effectively support the ability estimation of low and high orbit infrared detection satellites and achieve closed-loop analysis from load indicators to detection capability.

Openalex Percentile: Top 67%
Infrared Target Detection Methodologies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.