Multi-resolution model correction for improving the accuracy of flying laser ranging sensor

More and more unexpected incidents come out currently. Static sensor networks can not satisfy the increasing need for emergency response due to lack of adaptivity and limited coverage, thus mobile sensor networks become the research focus for overcoming above drawbacks. With excellent performances including autonomy, flexibility, stability and low-cost, micro-unmanned air vehicles (MUAVs) play a greater pole in mobile sensor networks. Ranging is one of the most critical sensing functions for mobile sensor networks. In this paper, a flying laser ranging sensor is proposed, essentially, an airborne pulsed time-of-flight (TOF) laser rangefinder (LRF) is realized. Because of the influence from walk error, time jitter, temperature drift and other factors, there is still room to improve the measurement precision of pulsed TOF LRFs. So the more important contribution of the paper is to present a novel interval time amendment approach for higher ranging precision. Based on leading-edge time discrimination, this method first employs wavelet multi-resolution analysis to compute compensation time values, which are computed mainly from local modulus maxima (LMMs) position differences. With approximations signals similarity and measurement relative error (MRE), a fusion evaluation is built to select the best wavelet parameters, and optimal corrected measurement model is obtained. Results show that MRE of the improved model is reduced by 73.41%. Therefore, the performance of flying laser ranging sensor is improved significantly with multi-resolution model correction.