Adaptive Two-Step Bearing-Only Underwater Uncooperative Target Tracking with Uncertain Underwater Disturbances

Abstract

The bearing-only tracking of an underwater uncooperative target can protect maritime territories and allows for the utilization of sea resources. Considering the influences of an unknown underwater environment, this work aimed to estimate 2-D locations and velocities of an underwater target with uncertain underwater disturbances. In this paper, an adaptive two-step bearing-only underwater uncooperative target tracking filter (ATSF) for uncertain underwater disturbances is proposed. Considering the nonlinearities of the target’s kinematics and the bearing-only measurements, in addition to the uncertain noise caused by an unknown underwater environment, the proposed ATSF consists of two major components, namely, an online noise estimator and a robust extended two-step filter. First, using a modified Sage-Husa online noise estimator, the uncertain process and measurement noise are estimated at each tracking step. Then, by adopting an extended state and by using a robust negative matrix-correcting method in conjunction with a regularized Newton-Gauss iteration scheme, the current state of the underwater uncooperative target is estimated. Finally, the proposed ATSF was tested via simulations of a 2-D underwater uncooperative target tracking scenario. The Monte Carlo simulation results demonstrated the reliability and accuracy of the proposed ATSF in bearing-only underwater uncooperative tracking missions.

An Efficient Underwater Navigation Method Using MPC with Unknown Kinematics and Non-Linear Disturbances

“…we can obtain a very compact formulation for problem (8) using an MPC approach as follows: (14) which can be further simplified by noting that we can replace s by its definition using the transition function in the restrictions, to obtain:…”

“…Finally, another challenge that arises in the underwater medium is related to the presence of unknown disturbances that affect the motion of the AUV. This brings additional difficulties to the location of the AUV [13,14], and hence, has been addressed by many works, such as [12,[15][16][17][18][19] or [20]. However, all these works either consider that the kinematics are known, which simplifies the problem [15,16,[18][19][20], or the algorithm proposed requires a high computational capacity on the AUV (e.g., references [12,15,17] require training neural networks), so these algorithms are unfeasible for low-capacity AUVs.…”

Performance Comparison of ToA and TDOA Based Tracking In Underwater Multipath Environments Using Bernoulli Filter

“…Several approaches exist for underwater localization, such as hydrodynamic pressure measurements [7], Angleof-Arrival (AoA), Time-of-Arrival (ToA), Time-Differenceof-Arrival (TDoA), and Received-Signal-Strength (RSS) [8]- [11]. The performances of these approaches depend on the applications, environment and sensor types [12].…”

Intelligence-Aware Batch Processing for TMA with Bearings-Only Measurements

“…Among other approaches, bearing-only target tracking [11][12][13] represents an increasingly popular topic, with application scenarios ranging from underwater tracking [14,15] to cooperative tracking for multiagent systems [15][16][17][18].…”