This paper addresses the problem of spectral analysis on radar measurements using high resolution methods. These methods have already been shown to yield better results than Fast Fourier Transform (FFT) based methods for accuracy on detected frequencies and more particularly for frequency resolution. In most applications, these performances are closely related to the performances of range and velocity estimation. In the paper, theoretical study shows the interest of subband decomposition for improving performances of frequency estimation in the case of the use of High Resolution methods, while it is shown to be inefficient when using FFT-based algorithms. Some elements of computational cost are given, in order to compare fullband and subband processing when using Fast Least Square Autoregressive (AR) algorithm. Finally, experimental results are given, showing the interest of subband decomposition within the frame of radar signal processing either for accuracy and resolution on frequency estimation.
Improving high resolution spectral analysis methods for radar measurements using subband decomposition
Verbesserung von Verfahren der hochauflösenden Spektralanalyse für den Einsatz bei Radarmessungen mit Hilfe der Subbandzerlegung
2005
5 Seiten, 4 Bilder, 14 Quellen
Conference paper
English
British Library Conference Proceedings | 2005
|On the use of high resolution spectral analysis methods in radar automotive
Tema Archive | 2004
|NTRS | 1994
|High-resolution spectral estimation algorithms in OFDM radar
Tema Archive | 2011
|