A Novel Recursive Empirical Frequency-domain Optimal Parameter Estimate Method Based on Reduced-order Matrix Approximation

The empirical frequency-domain optimal parameter (EFOP) estimate is a class of identification method combining the time-domain and the frequency-domain, which has the advantages of strong anti-disturbance and precise parameters identification, even with fewer samples. Aiming to improve the estimation accuracy of the existing recursive EFOP (REFOP) algorithm in the case of weak input signal, this paper proposes a novel REFOP estimate algorithm by modifying the recursive form of the weighted matrix. To improve the efficiency of the proposed algorithm, the technique of reduced-order matrix approximation is employed to alleviate the increased computation burden caused by the modification. The extensive simulations show that compared with the existing REFOP algorithm, the proposed one can perform faster and more precise parameters estimation whether the input signal is weak or not, which verifies its effectiveness and superiority sufficiently.