Robot motion estimation improves underwater sonar accuracy
Underwater sonar system is currently the best solution to distinguish a hazardous target from the harmless objects or a flock of fish at a far distance in the water, subsequently protect the harbors' security. A good sonar system should have the ability to survey a long range, in the meantime reserve a high accuracy. Noise is a crucial problem affecting the accuracy. One possible solution to increase the signal-to-noise ratio (SNR) is to average return signals over multiple sonar pings. A problem with this approach is the relative motion between the sonar and the target during pinging which strongly reduces the effect of the averaging. In this paper, we present a robust motion estimation using multiple receive sensors that estimates the relative motion between multiple pings and aligns all the pings to a base ping through appropriate motion compensation. We further show that the fusion of multiple pings for time-delay estimation after realignment has the potential of improving both the resilience to noise and the accuracy, consequently increasing the operating range