Abstract
This paper investigates the problem on simultaneously estimating the velocity and position of the target for range-based multi-USV positioning systems. According to the range measurement and kinematics model of the target, we formulate this problem in a mixed linear/nonlinear discrete-time system. In this system, the input and state represent the velocity and position of the target, respectively. We divide the system into two components and propose a three-step minimum variance unbiased simultaneous input and state estimation (SISE) algorithm. First, we estimate the velocity in the local level plane and predict the corresponding position. Then, we estimate the velocity in the heave direction. Finally, we estimate the 3-dimensional (3D) velocity and position. We establish the unbiased conditions of the input and state estimation for the MLBL system. Simulation results illustrate the effectiveness of the problem formulation and demonstrate the performance of the proposed algorithm.
Highlights
Since electromagnetic signal decays quickly in the water, the well-known GPS cannot be used [1, 2]
In this paper, we propose a method to simultaneously estimate the velocity and position of the target based on simultaneous input and state estimation (SISE)
Fang et al analysed the stability conditions of SISE algorithms for linear discrete-time systems with/without direct feedthrough [36]. Among all these SISE algorithms, the input is obtained by least square estimation and the state estimation problem is transformed into a KF problem
Summary
Since electromagnetic signal decays quickly in the water, the well-known GPS cannot be used [1, 2]. In this paper, we propose a method to simultaneously estimate the velocity and position of the target based on simultaneous input and state estimation (SISE). Fang et al analysed the stability conditions of SISE algorithms for linear discrete-time systems with/without direct feedthrough [36] Among all these SISE algorithms, the input is obtained by least square estimation and the state estimation problem is transformed into a KF problem. The main objective of this paper is to design a simultaneous velocity and position estimation method for range-based multi-USV positioning system. We formulate the positioning system in a mixed linear/nonlinear discrete-time system In this system, the velocity and position of the target are seen as the input and state, respectively. The unbiased minimum variance velocity and position estimation algorithms are designed in Sections 3 and 4, respectively.
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