A New Compact Delay, Doppler Stretch and Phase Estimation CRB with a Band-Limited Signal for Generic Remote Sensing Applications

• Published in: Remote sensing (Basel, Switzerland) Vol. 12; no. 18; pp. 2913 - 2936
• Main Authors: Das, Priyanka, Vilà-Valls, Jordi, Vincent, François, Davain, Loïc, Chaumette, Eric
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.09.2020; MDPI
• Subjects: Antennas; band-limited signals; Bandwidths; Broadband; Cramer-Rao bounds; Cramér–Rao bound; Delay; Doppler effect; Doppler effect and phase estimation; Engineering Sciences; Frequency shift; GNSS remote sensing; Lower bounds; maximum likelihood; Maximum likelihood estimators; Narrowband; Noise; Receivers & amplifiers; Remote sensing; Remote sensing systems; Remote sensors; Signal and Image processing; Signal to noise ratio; Taylor series; time-delay; Transmitters; Doppler effect and phase estimation; Time-delay; GNSS remote sensing; Maximum likelihood; Band-limited signals; Cramér–Rao bound
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs12182913

Since time-delay, Doppler effect and phase estimation are fundamental tasks in a plethora of engineering fields, tractable lower performance bounds for this problem are key tools of broad interest for a large variety of remote sensing applications. In the large sample regime and/or the high signal-to-noise ratio regime of the Gaussian conditional signal model, the Cramér–Rao bound (CRB) provides an accurate lower bound in the mean square error sense. In this contribution, we introduce firstly a new compact CRB expression for the joint time-delay and Doppler stretch estimation, considering a generic delayed and dilated band-limited signal. This generalizes known results for both wideband signals and the standard narrowband signal model where the Doppler effect on the band-limited baseband signal is not considered and amounts to a frequency shift. General compact closed-form CRB expressions for the amplitude and phase are also provided. These compact CRBs are expressed in terms of the baseband signal samples, making them especially easy to use whatever the baseband signal considered, therefore being valid for a variety of remote sensors. The new CRB expressions are validated in a positioning case study, both using synthetic and real data. These results show that the maximum likelihood estimator converges to the CRB at high signal-to-noise ratios, which confirms the exactness of the CRB. The CRB is further validated by comparing the ambiguity function and its 2nd order Taylor expansion where the perfect match also proves its exactness.