Vol. 3 Issue 3
Year:2015
Issue:Jul-Sep
Title:Detection and Estimation of Range, Velocity and Direction of Arrival of Multiple Targets
Author Name:N. Padmaja
Synopsis:
A novel method for Multiple target localization based on linear canonical transform is presented in this paper. It involves a modal preprocessing step to transform the signals received at the sensor array into signals at different modes, where narrowband techniques for DOA estimation can be applied. The incorporation of the fractional Fourier transform in the proposed method makes it possible to estimate the parameters of multiple targets even in challenging scenarios such as low SNR and closely spaced targets. Detection and estimation of Range, Velocity and Direction Of Arrival (DOA) of multiple far field targets using wideband chirp signals using ROOT-MUSIC algorithm reduces the error for DOA, Range and Velocity. The proposed method is better than the existing method. While comparing Raleigh channel with Root- MUSIC algorithm where errors like PAPR, CFO and STO are minimized. Proposed method gives more accurate results with low Root-Mean-Square Errors in the parameters estimated under complex conditions such as closely spaced targets and low Signal-to-Noise-Ratio.
Year:2015
Issue:Jul-Sep
Title:Detection and Estimation of Range, Velocity and Direction of Arrival of Multiple Targets
Author Name:N. Padmaja
Synopsis:
A novel method for Multiple target localization based on linear canonical transform is presented in this paper. It involves a modal preprocessing step to transform the signals received at the sensor array into signals at different modes, where narrowband techniques for DOA estimation can be applied. The incorporation of the fractional Fourier transform in the proposed method makes it possible to estimate the parameters of multiple targets even in challenging scenarios such as low SNR and closely spaced targets. Detection and estimation of Range, Velocity and Direction Of Arrival (DOA) of multiple far field targets using wideband chirp signals using ROOT-MUSIC algorithm reduces the error for DOA, Range and Velocity. The proposed method is better than the existing method. While comparing Raleigh channel with Root- MUSIC algorithm where errors like PAPR, CFO and STO are minimized. Proposed method gives more accurate results with low Root-Mean-Square Errors in the parameters estimated under complex conditions such as closely spaced targets and low Signal-to-Noise-Ratio.
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