Title :
Composite stochastic model for EMI-identification
Author_Institution :
FEL MCEME, Secunderabad, India
Abstract :
The detection of EMI in a radar can be found from an adaptive technique. Stochastic parameters are analytically derived for a complex EMI quantity. The PDF of the amplitude and phase are double bounded processes which can be determined theoretically. The instantaneous phases and amplitudes of this complex signal are related by the Hilbert transform pair. Autocorrelation of the amplitude is evaluated. An adaptive process based on autocorrelation is used to recover a desired signal in the EMI environment
Keywords :
Hilbert transforms; adaptive signal detection; amplitude estimation; correlation methods; electromagnetic interference; phase estimation; probability; radar detection; radar interference; stochastic processes; EMI detection; EMI environment; EMI identification; Hilbert transform pair; PDF; adaptive process; adaptive technique; autocorrelation; complex signal; composite stochastic model; double bounded processes; instantaneous amplitudes; instantaneous phases; radar; signal recovery; stochastic parameters; Autocorrelation; Density functional theory; Probability; Radar antennas; Radar detection; Random variables; Signal processing; Standards development; Stochastic processes; Upper bound;
Conference_Titel :
Electromagnetic Interference and Compatibility, 1995., International Conference on
Conference_Location :
Madras
Print_ISBN :
0-7803-3229-6
DOI :
10.1109/ICEMIC.1995.501586
