When detecting moving targets via photon counting Lidar, the target information contained in the echo photon statistical histogram is distorted, because the target position in a cumulative time changes. To solve the above distortion, this work proposed a method of acquiring moving target structural characteristics from the photon echo statistical histogram via waveform processing. Firstly, the probability distribution model of photon detection echo corresponding to a moving target was established. Then, the mathematical expressions of the laser radar cross section (LRCS) and depth structure corresponding to a moving target were derived by utilizing the photon waveform correction and waveform fitting filtering. Finally, the structural characteristics of a multi-layer moving target with a speed of 20m/s at 10km were obtained. Under the condition of SNR (signal-to-noise ratio) being 1.48, to detect a multi-layer moving target composed of two sub-targets with 0.5×1m, between which the distance was 0.5m, when the detection time was 0.01s (i.e., the cumulative number was 300), the consequential LRCS was 1.009m², and the ratio of LRCS within the moving target was 0.967:1. Meanwhile, the depth within the sub-targets was 0.493m, whose error was less than 0.7%. The proposed method in this work provided theoretical support for the acquisition of moving target detail information and the recognition of moving targets.
For detecting long-distance moving aerial targets, in order to solve the problem of low accumulation times and weak echo signal, this work proposes a multi-beam staring photon detection method. Firstly, the photon waveform expression of multi-beam staring photon detection is deduced. Then, the relationships between divergence angle, pulse width, single pulse energy, laser repetition frequency and photon probability distortion are discussed. Finally, the method of calculating the system transmitter parameters is obtained. The results show that when the detection target is the F22 flight with a speed of 400m/s at a distance of 10km, the number of beams is set to 40, the launch angle is set to 2mrad, the pulse width is set to 1ns, and the single pulse energy is set to 0.5μJ at the transmitting end. The research results provide a theoretical basis for the system design and realization of long-distance and fast-moving aerial targets.
The space environment is becoming increasingly complicated; therefore, precise detection and identification of space targets are critical to preserving space security. Compared to optical and radar imaging, obtaining space target information using laser echo waveform is more efficient for detection. Based on the skew-normal distribution decomposition, the connection between sub-echoes and target scale following the decomposition of the space target pulse laser echo waveform is explored, and an inversion approach is suggested to identify the scale information of the solar panel utilizing the intersection of skewness and kurtosis contours in the coordinate system of the variables to be solved, based on the high-order moment characteristics of waveforms such as skewness and kurtosis. Using the proposed method, we realized the scale inversion of a 60-cm solar panel of a cube satellite inclined at 45 deg, with the turntable and the detection system placed 80 m apart. The results show that the skewness and kurtosis of the decomposed echo can represent the target size information, and the approach used here can successfully extract the solar panel scale information of a typical satellite, providing methods and data support for space target detection and classification.
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