The adaptive robust algorithms of signal detection under different conditions of a priori uncertainty are synthesized for two adequate models of harmonic signal, namely autoregressive and trigonometric. The problem of detecting a harmonic signal with unknown parameters and estimation of its frequency against the background of uncorrelated Gaussian noise of unknown power is considered. This article concentrates on investigations of the synthesized detectors efficiency and robustness using the Monte Carlo method.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Adaptive Harmonic Signal Detecting Using Autoregressive Model


    Contributors:


    Publication date :

    2021-10-19


    Size :

    356090 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Spiral Autoregressive Model of a Quasiperiodic Signal

    Krasheninnikov, V. R. / Kalinov, D. V. / Pankratov, Y. G. | British Library Online Contents | 2001


    Adaptive Limit-checking for Spacecraft using Relevance Vector Autoregressive Model

    Fujimaki, R. F. / Yairi, T. Y. / Machida, K. M. et al. | British Library Conference Proceedings | 2005


    Polarimetric Sensitive Array Processing Using Autoregressive Signal Estimation

    Schneider, R. / Wanielik, G. / Electromagnetics Academy et al. | British Library Conference Proceedings | 1993


    Simulation of Neuron Adaptive Detecting System for Harmonic Current

    Wang, Q. / Wu, N. / Wang, Z. | British Library Online Contents | 1999


    Detecting Anomalies in Traction Motor Bearing Using Multi-scale Segmented Autoregressive Network

    Liu, Qi / Tian, Yin / Tang, Haichuan et al. | Springer Verlag | 2024