Navigation Solution with Wavelet Denoising and Allan Variance Estimation
Recent advent of micromachining revolutionized the conventional Inertial Navigation applications. From robotics, biomedical equipment and mining to high precision aerospace applications, low cost, easily manufactured Micro Electro Mechanical Systems (MEMS) inertial sensors had made their way with partial success. Although their synergism with GPS proved beneficial in most cases ,GPS overall un reliability and frequent outages forced research scholars to design intelligent stochastic error modeling techniques to account for time dependent ,huge ,non Gaussian, uncorrelated and environment dependent errors .The Noise behavior of MEMS can be divided broadly divided in high frequency and low frequency types. This paper explores Allan variance technique in characterizing low frequency stochastic errors in addition with Wavelet Denoising technique to filter high frequency noise or white noise. After using these techniques with Extended Kalman Filter, Integration of GPS with 1MU gave significant improvement in presence of GPS outages.
Allan Variance Wavelet Denoising MEMS Navigation
Siddiqui Saman Mukhtar Fang Jiancheng
School of Instrumentation Science and Optoelectronics Engineering Beihang University Beijing,China
国际会议
重庆
英文
401-406
2011-01-21（万方平台首次上网日期，不代表论文的发表时间）