With the deepening research on space exploration, the photoelectric reconnaissance technology of various space targets has made great progress. Although this technology has been gradually improved, the problem of high-precision reconnaissance for long-range space targets has not been well solved. At present, the mainstream space photoelectric detection system is still based on the traditional optical system, which is limited by its diffraction limit, effective aperture, and other factors. This space photoelectric reconnaissance technology based on the traditional optical imaging theory is usually unable to perform in the field of remote accurate detection and imaging. Laser reflective tomography imaging (LRTI), as a new remote and high-precision space target detection method, has more advantages in high-precision imaging of remote targets. 1) LRTI is easy to implement in principle and easy to construct system structure. 2) The imaging resolution of LRTI is mainly related to the pulse width of the emitted light, the performance of the detector, and the signal-to-noise ratio, but is relatively unrelated to the detection distance and receiving aperture. 3) LRTI adopts the method of direct detection. It mainly receives the energy information from the laser echo signal reflected by the target, which is relatively less interfered with by atmospheric turbulence and other factors. Thus, LRTI has better applicability and practicability, and better application prospect in remote detection. Additionally, the imaging optimization method as the core of LRTI becomes the focus of many researchers. At present, the optimization schemes for LRTI quality usually start from the reconstruction algorithm, rotation center registration, subsequent image processing, and so on, but cannot eliminate the influence of image artifacts caused by noise and waveform distortion caused by turbulence. The noise and distortion doped in the laser echo signal greatly reduce the image quality optimization effect of the above schemes, and result in more complicated algorithm processing. Therefore, it is of great significance to develop a LRTI optimization method that can start from the echo signals.

We study the related problems of LRTI quality optimization, apply the echo decomposition method to the LRTI optimization method, and propose a LRTI quality optimization method based on echo decomposition. This method aims to suppress the influence of waveform distortion and noise by adjusting and optimizing the waveform of laser echo signals. The proposed method employs layer by layer stripping method to decompose the laser echo signal into several waveform components and filter the waveform components containing target information through a preset noise threshold. After obtaining the wave components that meet the conditions, these wave components are combined to obtain a more real laser echo signal, and then the target image is reconstructed through the reconstruction algorithm.

We build an experimental platform for LRTI and collect the projection data of the cube at a distance of 200 m (Fig. 6). The method put forward in our study is adopted to optimize the laser echo signal, and then the target image is reconstructed through the filtered back projection (FBP) algorithm (Fig. 9). The results show that when the same set of projection data is utilized, the peak signal to noise ratio (PSNR) before and after optimization by the proposed method is 16.5 and 17.8 respectively, with improved quality of the reconstructed image. At the same time, in terms of subjective visual perception, the artifact and noise of the optimized image are significantly less than those of the original image. This shows that the optimization method of LRTI based on waveform decomposition can effectively improve the quality of the reconstructed image, and better eliminate the influence of most ring artifacts and noise in the reconstructed image. This conclusion is still applicable under different sampling angle intervals (Fig. 10).

We propose a method of LRTI based on laser echo waveform decomposition. By applying the waveform decomposition processing method to the LRTI technology, this method realizes the clutter elimination and waveform correction in the laser echo signal. In addition, a LRTI verification experiment with a detection distance of about 200 m is carried out to verify the application effect of the laser echo waveform decomposition method in LRTI. The experimental results indicate that in the LRTI technology applied in more complex environments, the introduction of the waveform decomposition method can better eliminate the influence of ring artifacts and most of the noise caused by clutter, and has sound application effects at different sampling angle intervals. This will help to improve the quality of the reconstructed images of LRTI technology.