Optimal Volterra-based nonlinear system identification using arithmetic optimization algorithm assisted with Kalman filter

Singh, Sandeep; Ashok, Alaknanda; Rawat, Tarun Kumar

doi:10.1007/s12530-022-09439-z

Cited by 6 publications

(1 citation statement)

References 52 publications

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“…To address the shortcomings of the KF in nonlinear filtering problems, optimization methods have been integrated into the KF framework, including the particle swarm optimization (PSO) [17], genetic algorithm (GA) [18], arithmetic optimization algorithm (AOA) [19], and cuckoo search algorithm (CSA) [20]. These are optimization algorithms assisted by a Kalman filter.…”

Section: Introductionmentioning

confidence: 99%

A Suboptimal Optimizing Strategy for Velocity Vector Estimation in Single-Observer Passive Localization

Luo

Chu³

et al. 2023

Sensors

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In a single-observer passive localization system, the velocity and position of the target are estimated simultaneously. However, this can lead to correlated errors and distortion of the estimated value, making independent estimation of the speed and position necessary. In this study, we introduce a novel optimization strategy, suboptimal estimation, for independently estimating the velocity vector in single-observer passive localization. The suboptimal estimation strategy converts the estimation of the velocity vector into a search for the global optimal solution by dynamically weighting multiple optimization criteria from the starting point in the solution space. Simulation verification is conducted using uniform motion and constant acceleration models. The results demonstrate that the proposed method converges faster with higher accuracy and strong robustness.

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