Cooperative navigation and localization for unmanned surface vessel with low-cost sensors

As one of the most promising research direction, cooperative location with high precision and low-cost IMU is becoming an emerging research topic in many positioning fields. Low-cost MEMS/DVL is a preferred solution for dead-reckoning in multi-USV cooperative network. However, large misalignment angles and large gyro drift coexist in low-cost MEMS that lead to the poor observability. Based on UKF, that access to high accuracy and relative small computation, dual-model filtering scheme is proposed. It divides the whole process into two subsections that cut off the coupling relations and improve the observability of MEMS errors: first estimates large misalignment angle and then estimates the gyro drift. Furthermore, to improve the convergence speed of large misalignment angle estimated in the first subsection, "time reversion" concept is introduced. It uses a short period time to forward and backward several times to shorten estimation time effectively. Finally, simulation results show that the algorithm can effectively improve the cooperative navigation performance.