Target Detection Of Three-Dimensional Laser Radar And Pose Estimation Of Passive Images

Avariety of civilian and military applications require recognizing stationary or moving objects, situated in unknown surroundings, using standard sensors such as three-dimensional laser radar,video sensor and forward-looking infrared sensors. The range value of the Forward-looking infrared sensors is father than laser radar. But a Forward-looking infrared sensor is a passive system, so its position can easily be discovered, the image is very instability and the false alarm probability is very high. Laser radar can present range image and intensity image, so it can accomplish the detection mission, but it also have flaw, the function of the range is very near.This paper aim at the theory and computer emulator of detecting object that use three-dimensional laser radar and the estimation of object's pose. And emphasize the theory of three-dimensional laser radar and Hilbert-Schmidt Bounds (HSB) for estimators on matrix Lie groups.First this paper introduces a three-dimensional laser radar and analyses the laser radar system, then introduces the forward-looking infrared (FLIR) system and its single pixel statistics. Then give the emulator thought of the three-dimensional laser radar range image. Using MATLAB calculate the relation between the objects cross section,carrier-to noise ratio,the range resolution and probability of detection, then paint relation curve of the parameters and the probability of detection.Secondly, this paper introduces the Hilbert-Schmidt Bounds (HSB) and mostly focuses on the express fashion of formable objects template and express fashion of matrix Lie group of automatic target recognition (ATR) system. Upon this frame, use matrix Lie group to express the rotation space, then base on Bayesian estimation framework, calculate the minimum mean squared error bounds which use the matrix Lie groups. Extend the expressions of the minimum mean squared error bounds of the references, and give the relations of the minimum mean squared error bounds of pose angle and noise standard deviation. In the end, calculate minimum mean squared error bounds which use the matrix Lie groups to express the object's orientation in the simple instance, and paint...