Tracking the key point of a building in infrared imaging guidance

2013 ◽  
Author(s):  
Yi-mei Tan ◽  
Fu-gen Zhou ◽  
Ting Jin
Keyword(s):  
Infrared Imaging ◽  
Imaging Guidance

Study on Dynamic IR Image Generation of Space Target

2014 ◽  
Vol 1044-1045 ◽  
pp. 1343-1348
Author(s):  
Wu Can He ◽  
Shou Yi Liao ◽  
Zuo Yu Zhang ◽  
He Xin Zhang
Keyword(s):  
Infrared Imaging ◽  
Three Dimensional ◽  
Orbit Space ◽  
Guidance System ◽  
Image Generation ◽  
Hardware In The Loop ◽  
Imaging Guidance ◽  
Infrared Star ◽  
Objective Basis ◽  
Space Target

Dynamic IR image generation of space target is one of the key technologies in hardware in the loop simulation for the infrared imaging guidance system. The three-dimensional entity model is created in the Creator, Sinda/Fluint is used to analyze each part of dynamic infrared radiation characteristics from on-orbit Space Target, on the basis of the LRS infrared star catalogues, celestial background modeling is built. In Vega, the dynamic IR image of space target is generated. The simulation results show that the dynamic IR image of Space Target provide the important objective basis for the hardware in the loop simulation for the infrared imaging guidance system.

An improved weak light detector used for infrared Imaging guidance system

Optik ◽  
2016 ◽  
Vol 127 (4) ◽  
pp. 2316-2318 ◽  
Author(s):  
Pengpeng Zhao ◽  
Shaohui Cui
Keyword(s):  
Infrared Imaging ◽  
Guidance System ◽  
Imaging Guidance ◽  
Light Detector ◽  
Weak Light

Infrared Target Tracking Based on Improved Particle Filtering

2020 ◽  
pp. 2154015
Author(s):  
Zhiwei Hu ◽  
Yixin Su
Keyword(s):  
Genetic Algorithm ◽  
Kalman Filter ◽  
Target Tracking ◽  
Extended Kalman Filter ◽  
Particle Filtering ◽  
Infrared Imaging ◽  
Guidance System ◽  
Accurate Estimation ◽  
Imaging Guidance ◽  
Particle Filter Algorithm

Infrared target tracking technology is one of the core technologies in infrared imaging guidance systems and is also a hot research topic. The problem of particle degradation could be always found in traditional particle filtering, and a large number of particles are additionally required for accurate estimation. It is difficult to meet the requirements of a modern infrared imaging guidance system for accurate target tracking. To solve the problem of particle degradation and improve the performance of infrared target tracking, the extended Kalman filter and genetic algorithm are introduced into particle filtering, and an improved algorithm for infrared target tracking is proposed in this paper. In the framework of a particle filter algorithm, the Gaussian distribution for each particle is generated and propagated by a separate extended Kalman filter to improve the sampling accuracy and effectiveness of the probability density function of particles. Genetic algorithm is used to perform a resampling process to solve particle degradation and ensure the diversity of particle states in particle swarm. Simulation results show that the improved tracking algorithm based on improved particle filtering proposed in this paper can effectively solve the phenomenon of particle degradation and track the infrared target.

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