This paper reviews the development and experimental evaluation of three techniques for estimating the alignment matrix of Doppler sonars, which are commonly used for precision navigation of oceanographic submersibles, employing sensors commonly employed aboard these vehicles. Most previously reported methods addressed the problem of single degree of freedom alignment using bottom-lock Doppler sonar data and global positioning system (GPS) navigation data. This paper reviews three techniques for three degree of freedom calibration of attitude and Doppler sonar sensors, using sensor data available to vehicles at full ocean depth. The first technique provides a general linear least-square estimate of the alignment matrix. The second technique is a least-squares estimate that results in an alignment matrix estimate belonging to the group of special orthogonal matrices. The third technique is a novel adaptive identifier that constrains the estimate to the group of special orthogonal matrices. The performance of these estimates is evaluated with a laboratory remotely operated vehicle (ROV) and a field deployed autonomous underwater vehicle (AUV). Experimental results are reported which demonstrate that Doppler navigation employing the reported alignment methods significantly improves navigation precision. The latter techniques provide calibration estimates which improve Doppler navigation precision not only on the calibration data set itself, but also improve precision over a wide variety of vehicle trajectories other than the calibration data set.
Kinsey, James C., "Advances in In-Situ Calibration of Attitude and Doppler Sensors for Precision Oceanographic Submersible Navigation" (2005). Link Foundation Ocean Engineering and Instrumentation Fellowship Reports. 7.