In the distributed optoelectronic system, when the optoelectronic reconnaissance equipments cooperates to locate the target, it needs to use the azimuth and elevation information of the optoelectronic reconnaissance equipments, which usually has measurement errors. This paper proposes a distributed optoelectronic system collaborative positioning model with measurement errors, and analyzes the influence of the measurement errors of azimuth and elevation on the target positioning error, At the same time, the influence of the baseline between the optoelectronic reconnaissance equipment on the target positioning error is analyzed. the influence of the included angle between and the positioning lines on the target positioning error is analyzed. The modeling analysis shows that the smaller the measurement error of azimuth and elevation angle are, the smaller the target positioning error is; The longer the baseline is, the smaller the target positioning error is; The closer the included angle of the positioning line is to 4/π, the smaller the target positioning error is. It provides a basis for the selection of angle measuring sensors in the distributed optoelectronic system and the layout of optoelectronic reconnaissance equipment in the distributed optoelectronic system.
In order to improve the anti-interference and tracking performance of photoelectric stabilized platform, a sliding mode controller based on reaching law was designed. Since the differential signal of the input was used in the sliding mode controller, if the noise was added in the input signal, its differential signal will amplify the noise, thus affecting the actual effect of the controller. To solve this problem, a method combining nonlinear Tracking Differentiator (TD) with sliding mode controller was proposed ,then the experimental system was built, and the results of the new controller and the traditional PID controller were compared. It is proved that the method this article presented can improve the anti-interference performance of the system by 66.7%, and also can increase the track precision of the input signal by 48.2%.
In the unmanned photoelectric reconnaissance vehicle network, each node cooperates to locate the target, which is beneficial to expand the reconnaissance range and obtain the target position information covertly. The unmanned photoelectric reconnaissance vehicle of each node can provide the angle information relative to the target when it reconnoitres the target. How to use the angle information of the target detected by each node to obtain the estimation of the target position information is worth studying. This paper studies the passive positioning technology in the unmanned photoelectric reconnaissance vehicle network, establishes the model of the unmanned photoelectric reconnaissance vehicle network for cooperative target positioning, and uses the least-squares method to design the target positioning algorithm. The error between the target position value and the true value is within 10m, which proves that the algorithm can effectively obtain the target position information, and provides an effective method for the hidden acquisition of target position information in the unmanned photoelectric reconnaissance vehicle network.
In order to meet the needs of border reconnaissance and surveillance tasks, improve the detection capability of moving target detection for vehicles, people and unmanned aerial vehicles in unattended environment. In this paper, a mechanism of photoelectric reconnaissance in unattended environment is proposed, which can realize the functions of space three-dimensional sector scanning reconnaissance, target detection, threat warning and so on. The technologies of area coverage, moving target detection and target false alarm involved in the mechanism are analyzed one by one. The coverage strategy of sector scan area suitable for unattended operation, the optimized moving target detection algorithm and the adaptive adjustment technology of optical field of view for targets with different characteristics are proposed. The experimental results show that the system can effectively detect the target with the above characteristics, improve the detection probability of the target and the accuracy of threat warning, and provide strong support for unattended environment.
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