Research On Echo Processing Method In Multi-pulse Remote Laser Ranging

Laser ranging technology has experienced nearly 60 years,and it has achieved a variety of technologies ranging from initial distance measurement to speed measurement,tracking,and guidance based on laser ranging technology.It plays an extremely important role in the military and defense fields.In the combat system,laser ranging is required to achieve long-distance and high-precision measurements.The application of the multi-pulse system laser creates a new situation for long-distance measurement.Since the laser ranging process is bound to be affected by noise,the signal to noise ratio of the laser ranging echo signal is often very low during long distance measurement,which is an important factor limiting the measurement distance.In this thesis,we mainly discuss the signal processing and detection of laser multi-pulse echo whose including multi-pulse superposition,wavelet transform,empirical mode decomposition,matched filtering and correlation detection techniques and the specific improvements were given.Aiming at the problem that the echo signals caused by the equal pulse interval in the traditional multiple pulse superposition technique cannot be accurately identified,a multiple pulse superposition method with non-uniform intervals was proposed;for the problem that the noise mode and the signal mode critical point existed in the empirical mode decomposition filtering method are difficult to determine,a filtering criterion based on the characteristics of the autocorrelation function was adopted,and the filtered noise mode was processed by the improved threshold wavelet denoising method to achieve signal denoising at low signal-to-noise ratios.Aiming at the problem of low signal-to-noise ratio of echo signals from remote laser ranging,analyzing the advantages and disadvantages of the above methods,a set of signal processing solution was proposed,combined non-uniform multi-pulse superposition technology,empirical mode decomposition and improved threshold wavelet denoising technology,cross-correlation detection technique,and finally we discussed the feasibility of the solution.