Bayesian Estimation of Smooth Altimetric Parameters: Application to Conventional and Delay/Doppler Altimetry

Abderrahim Halimi (1) , Corinne Mailhes (2, 3) , Jean-Yves Tourneret (4, 3) , Hichem Snoussi (1)

1 LM2S - Laboratoire Modélisation et Sûreté des Systèmes
2 IRIT-SC - Signal et Communications
3 Toulouse INP - Institut National Polytechnique (Toulouse)
4 IRIT-MINDS - CoMputational imagINg anD viSion

This paper proposes a new Bayesian strategy for the smooth estimation of altimetric parameters. The altimetric signal is assumed to be corrupted by a thermal and speckle noise distributed according to an independent and non-identically Gaussian distribution. We introduce a prior enforcing a smooth temporal evolution of the altimetric parameters which improves their physical interpretation. The posterior distribution of the resulting model is optimized using a gradient descent algorithm which allows us to compute the maximum a posteriori estimator of the unknown model parameters. This algorithm has a low computational cost that is suitable for real-time applications. The proposed Bayesian strategy and the corresponding estimation algorithm are evaluated using both synthetic and real data associated with conventional and delay/Doppler altimetry. The analysis of real Jason-2 and CryoSat-2 waveforms shows an improvement in parameter estimation when compared to state-of-the-art estimation algorithms.

Mots clés: Smooth estimation; Simultaneous autoregression (SAR) altimetry; Bayesian algorithm; Delay/Doppler altimetry (DDA); Coordinate descent algorithm; Natural gradient; Altimetry

Domaines: Traitement du signal et de l'image [eess.SP]

Abderrahim Halimi, Corinne Mailhes, Jean-Yves Tourneret, Hichem Snoussi. Bayesian Estimation of Smooth Altimetric Parameters: Application to Conventional and Delay/Doppler Altimetry. IEEE Transactions on Geoscience and Remote Sensing, 2016, vol. 54 (n° 4), pp. 2207-2219. ⟨10.1109/TGRS.2015.2497583⟩. ⟨hal-01311346⟩