Conceptual Design and Image Motion Compensation Rate Analysis of Two-Axis Fast Steering Mirror for Dynamic Scan and Stare Imaging System

In order to enable the aerial photoelectric equipment to realize wide-area reconnaissance and target surveillance at the same time, a dual-band dynamic scan and stare imaging system is proposed in this paper. The imaging system performs scanning and pointing through a two-axis gimbal, compensating the image motion caused by the aircraft and gimbal angular velocity and the aircraft liner velocity using two two-axis fast steering mirrors (FSMs). The composition and working principle of the dynamic scan and stare imaging system, the detailed scheme of the two-axis FSM and the image motion compensation (IMC) algorithm are introduced. Both the structure and the mirror of the FSM adopt aluminum alloys, and the flexible support structure is designed based on four cross-axis flexural hinges. The Root-Mean-Square (RMS) error of the mirror reaches 15.8 nm and the total weight of the FSM assembly is 510 g. The IMC rate equations of the two-axis FSM are established based on the coordinate transformation method. The effectiveness of the FSM and IMC algorithm is verified by the dynamic imaging test in the laboratory and flight test.

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Line of Sight and Image Motion Compensation for Step and Stare Imaging System

Applied Sciences ◽

10.3390/app10207119 ◽

2020 ◽

Vol 10 (20) ◽

pp. 7119

Author(s):

Jihong Xiu ◽

Pu Huang ◽

Jun Li ◽

Hongwen Zhang ◽

Youyi Li

Keyword(s):

High Resolution ◽

Motion Compensation ◽

Imaging System ◽

Control Flow ◽

Image Motion ◽

Line Of Sight ◽

Pointing Accuracy ◽

High Resolution Images ◽

Pointing Control ◽

And Control

In recent years, applications such as marine search and rescue, border patrol, etc. require electro-optical equipment to have both high resolution and precise geographic positioning abilities. The step and stare working based on a composite control system is a preferred solution. This paper proposed a step and stare system composed of two single-axis fast steering mirrors and a two-axis gimbal. The fast steering mirrors (FSMs) realize image motion compensation and the gimbal completes pointing control. The working principle and the working mode of the system are described first. According to the imaging optical path, the algorithm and control flow of the line of sight (LOS) and image motion compensation are developed. The proposed method is verified through ground imaging and flight tests. Under the condition of flight, the pointing accuracy of the target can be controlled within 15 m. The proposed algorithm can achieve effective motion compensation and get high-resolution images. This achieves high resolution and accurate LOS simultaneously.

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Study of image motion compensation in spectral imaging system

10.1117/12.2243460 ◽

2016 ◽

Author(s):

Zhijun Li ◽

Xing Long Chen

Keyword(s):

Motion Compensation ◽

Imaging System ◽

Spectral Imaging ◽

Image Motion

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Design of Dual-band Cavity Filter Using Frequency Transformation Method

JOURNAL OF ELECTRONICS INFORMATION TECHNOLOGY ◽

10.3724/sp.j.1146.2011.01151 ◽

2012 ◽

Vol 34 (6) ◽

pp. 1489-1493

Author(s):

Xin Kou ◽

Zhong-yin Xiao ◽

Chun-yan Huang ◽

Hao Li ◽

Jun-jun Chu

Keyword(s):

Transformation Method ◽

Dual Band ◽

Frequency Transformation

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Efficient onboard image motion compensation for orbital inclination and eccentricity of geostationary weather satellites

Proceedings of the Institution of Mechanical Engineers Part G Journal of Aerospace Engineering ◽

10.1177/0954410019900706 ◽

2020 ◽

Vol 234 (7) ◽

pp. 1311-1325

Author(s):

MP Ramachandran ◽

MK Agarwal ◽

DA Daniel

Keyword(s):

Motion Compensation ◽

Satellite Images ◽

Software Tool ◽

Image Motion ◽

Wind Vector ◽

Orbital Inclination ◽

Scanning Mirror ◽

The Earth ◽

Detail Image ◽

Geographical Locations

Image registration is important in geostationary weather satellites. Achieving consistent registration of the images with respect to the geographical locations on the Earth is here of interest. The consistency in the registration between the images is affected whenever the orbital inclination and eccentricity are not zero. The imaging payload has a two-axis scanning mirror to capture the Earth image. The above orbital effects together with scan mirror pointing direction are the factors that cause the misregistration. This paper presents an onboard algorithm that provides the scan compensation angles due to the above factors and achieves consistent registration. The compensation varies every second, which is the time taken for each scan. Hence it is preferred to have computations onboard than to have ground based bulk uplinks for the scan compensation. The paper presents an algorithm that is useful, say, when (i) the onboard computing capabilities are limited, (ii) the navigation accuracies are coarse and (iii) the image resampling is not preferred on the ground and the payload data are directly used for weather applications. The paper also discusses the tests that were carried on the onboard software in order to validate its performance in achieving the consistent registration before launch. This is done by using another independent software tool which is also described in detail. Image motion algorithm was invoked for a couple of days in INSAT 3DR. The atmospheric wind vector deduced directly from the satellite images is given at the end.

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Crack Detection on a Retaining Wall with an Innovative, Ensemble Learning Method in a Dynamic Imaging System

Sensors ◽

10.3390/s19214784 ◽

2019 ◽

Vol 19 (21) ◽

pp. 4784 ◽

Cited By ~ 1

Author(s):

Chern-Sheng Lin ◽

Shih-Hua Chen ◽

Che-Ming Chang ◽

Tsu-Wang Shen

Keyword(s):

Ensemble Learning ◽

Crack Detection ◽

Imaging System ◽

Retaining Wall ◽

Local Binary Patterns ◽

Dynamic Imaging ◽

Learning Method ◽

Unmanned Vehicle ◽

Feature Values ◽

A Charge

In this study, an innovative, ensemble learning method in a dynamic imaging system of an unmanned vehicle is presented. The feasibility of the system was tested in the crack detection of a retaining wall in a climbing area or a mountain road. The unmanned vehicle can provide a lightweight and remote cruise routine with a Geographic Information System sensor, a Gyro sensor, and a charge-coupled device camera. The crack was the target to be tested, and the retaining wall was patrolled through the drone flight path setting, and then the horizontal image was instantly returned by using the wireless transmission of the system. That is based on the cascade classifier, and the feature comparison classifier was designed further, and then the machine vision correlation algorithm was used to analyze the target type information. First, the system collects the target image and background to establish the samples database, and then uses the Local Binary Patterns feature extraction algorithm to extract the feature values for classification. When the first stage classification is completed, the classification results are target features, and edge feature comparisons. The innovative ensemble learning classifier was used to analyze the image and determine the location of the crack for risk assessment.

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