Analysis of a Maximum Likelihood Phase Estimation Method for Airborne Multibaseline SAR Interferometry

Magnard, Christophe; Frioud, Max; Small, David; Brehm, Thorsten; Meier, Erich

doi:10.1109/jstars.2015.2487685

Cited by 20 publications

(8 citation statements)

References 28 publications

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“…In general, the estimation of the unknowns of the baseline error model described by (5) can be performed individually for the data of each frequency of acquisition. However, airborne repeat-pass interferometric phases are often affected by higher order spatially correlated errors not accounted for in this model.…”

Section: A General Calibration Approachmentioning

confidence: 99%

“…φ XS diff is the observation of the difference between the X-and S-band repeat-pass phases (19) and the forward operators A * are constructed according to the model in (5).…”

Section: A General Calibration Approachmentioning

confidence: 99%

“…In addition to the already cited literature, [16] investigated an ML approach to combine single-pass multibaseline/multiaspect data sets to obtain the elevation models of urban areas using the MEMPHIS Ka-band sensor. Moreover, [5] and [31] studied several aspects of the SAR and InSAR processing chains for MEMPHIS Ka-band data, including the efficiency of ML height estimators.…”

Section: Introductionmentioning

confidence: 99%

“…In fact, several airborne SAR systems have been used recently to retrieve accurate topographic information. For example, the aforementioned works [5], [31] reported a relative vertical accuracy varying from 19 to 59 cm (one standard deviation), depending on the characteristics of the acquisition, and an effective coverage area of around 2.1 km × 0.6 km (azimuth × range) using data from the Memphis Ka-band system. De Macedo et al [41] demonstrated the importance of using topography-and-aperture-dependent Motion Compensation (MoCo) to retrieve accurate height measurements over challenging terrain using the single-pass/three-baseline configuration of the OrbiSAR sensor.…”

Section: Introductionmentioning

confidence: 99%

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Generation of Highly Accurate DEMs Over Flat Areas by Means of Dual-Frequency and Dual-Baseline Airborne SAR Interferometry

Pinheiro

Reigber

Scheiber

et al. 2018

IEEE Trans. Geosci. Remote Sensing

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In this paper, a dual-frequency and dual-baseline (DFDB) processing framework for the extraction of highprecision terrain information from airborne interferometric synthetic aperture radar (SAR) data is presented. Specifically, we propose the use of two single-pass data sets acquired simultaneously in two different frequency bands and two largebaseline repeat-pass data sets also acquired simultaneously in two frequency bands. The configuration profits from the stability of the single-pass derived elevation maps in relation to spatially correlated artifacts as well as from the increased sensitivity associated with large-baseline acquisitions. Moreover, the dualfrequency nature of the data set enables the tackling of the phase unwrapping issue, promoting the retrieval of unambiguous measurements. Several algorithms for the interferometric processing of the DFDB airborne data set are proposed, including the outline of multichannel phase calibration and unwrapping error correction strategies and approaches to remove spatially correlated artifacts and extract the common underlying topography. Elevation models generated from a DFDB data set acquired with the airborne F-SAR sensor over tidal flats in northern Germany are presented, and comparisons with an airborne laser scanner reference show errors with a standard deviation of around 14 cm and a mean absolute deviation of less than 10 cm. Index Terms-Digital elevation model (DEM), dual frequency, repeat-pass interferometry, SAR interferometry (InSAR). 0196-2892

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Section: A General Calibration Approachmentioning

confidence: 99%

“…φ XS diff is the observation of the difference between the X-and S-band repeat-pass phases (19) and the forward operators A * are constructed according to the model in (5).…”

Section: A General Calibration Approachmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Generation of Highly Accurate DEMs Over Flat Areas by Means of Dual-Frequency and Dual-Baseline Airborne SAR Interferometry

Pinheiro

Reigber

Scheiber

et al. 2018

IEEE Trans. Geosci. Remote Sensing

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“…Examples of such systems are the C-/X-Band F-SAR [12], the X-Band PAMIR [13], the X-/Ku-Band RAMSES [14], the X-Band SETHI [15], the X-Band OrbiSAR [9] and the Ka-Band MEMPHIS [16][17][18][19][20]. As a matter of fact, in these systems the InSAR baseline can be as small as required by the geometrical constraints imposed by small airborne platforms.…”

Section: Introductionmentioning

confidence: 99%

The InSAeS4 Airborne X-Band Interferometric SAR System: A First Assessment on Its Imaging and Topographic Mapping Capabilities

Perna

Esposito

Amaral³

et al. 2016

Remote Sensing

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We present in this work a first assessment of the imaging and topographic mapping capabilities of the InSAeS4 system, which is a single-pass interferometric airborne X-Band Synthetic Aperture Radar (SAR). In particular, we first provide a brief description of the InSAeS4 sensor. Then, we discuss the results of our analysis on the SAR and interferometric SAR products relevant to the first flight-test campaign. More specifically, we have exploited as reference the GPS measurements relevant to nine Corner Reflectors (CRs) deployed over the illuminated area during the campaign and a laser scanner Digital Elevation Model (DEM). From the analysis carried out on the CRs we achieved a mean geometric resolution, for the SAR products, of about 0.14 m in azimuth and 0.49 m in range, a positioning misalignment with standard deviation of 0.07 m in range and 0.08 m in azimuth, and a height error with standard deviation of 0.51 m. From the comparison with the laser scanner DEM we estimated a height error with standard deviation of 1.57 m.

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Nonhomogeneous clutter suppression based on terrain elevation interferometric phase compensation in multi-satellite formation systems

Yang

et al. 2022

Digital Signal Processing

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Analysis of a Maximum Likelihood Phase Estimation Method for Airborne Multibaseline SAR Interferometry

Cited by 20 publications

References 28 publications

Generation of Highly Accurate DEMs Over Flat Areas by Means of Dual-Frequency and Dual-Baseline Airborne SAR Interferometry

Generation of Highly Accurate DEMs Over Flat Areas by Means of Dual-Frequency and Dual-Baseline Airborne SAR Interferometry

The InSAeS4 Airborne X-Band Interferometric SAR System: A First Assessment on Its Imaging and Topographic Mapping Capabilities

Nonhomogeneous clutter suppression based on terrain elevation interferometric phase compensation in multi-satellite formation systems

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