Abstract
We consider the problem of tracking a surface magnetic ship as it travels in a straight line path with the exertion of a magnetometer located at the seabed. Note that the initial filter parameters are prior information and the tracking performance depends on the initial filter parameters, and traditional estimation of initial filter parameters is to apply the filter bank algorithm, but there are several obvious defects in this method. In this paper, a novel algorithm based on the particle swarm optimization (PSO) algorithm is proposed to estimate initial parameters of the filter, and the model of uniformly magnetized ellipsoid is adopted to fit the magnetic field of the ship. The simulation results show that, under the condition of no prior information, the estimated ship parameters based on the observation of the single-observer are invalid, whereas the estimated ship parameters based on the observation of the double-observer are valid. Further, the estimated results of real-world recorded magnetic signals show that the ship parameters estimated by PSO based on the double-observer are also valid, as the estimated parameters are used as the initial parameters of the unscented Kalman filter (UKF), and a ship can be tracked effectively by the UKF filter. Moreover, the estimated half focal length can be used as a feature to distinguish noise environment, ships with different sizes, and mine sweepers.
Highlights
As for the shadowing filter [8, 9], the optimization is based on a series of observed data by the Lagrange multiplier method or the gradient descent method
One is that the initial parameters of each filter still needs to be set based on the experience, and the number of filters is limited; the second is that only the ship is close to the CPA point, and the selected filter can be determined, but the real-time tracking distance of the magnetic target is sacrificed; third, even when the filter is selected, there is a nonnegligible deviation between the initial parameters and the true parameters, which results in poor performance of the subsequent tracking
Based on the measurement of double magnetometers, the particle swarm optimization (PSO) algorithm is employed to estimate the initial parameters of target parameters. e optimization space, population iteration times, and population size parameters are consistent with Section 3.1. e estimated results are shown in Table 2, where the motion reference parameters are GPS positioning results
Summary
Where i denotes the different magnetometers; j denotes the different measuring points; Mx, My, and Mz are the magnetic moment in the x, y, and z directions of the uniformly magnetized ellipsoid;. (axij, ayij, azij, bxij, byij, bzij, cxij, cyij, czij) are the corresponding magnetic field calculation coefficients of the uniformly magnetized ellipsoid, where axij. Considering the motion property of the ship in a short period, it is assumed that the ship moves uniformly and in a straight line in the coordinate system O1XYZ, where VX and
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