Performance Requirements for Ionospheric Correction of Low-Frequency SAR Data

Meyer, Franz J.

doi:10.1109/tgrs.2011.2146786

Cited by 108 publications

(78 citation statements)

References 31 publications

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“…FR transfers backscattered energy between the four polarization channels, and if it is not corrected to better than 5 • , derived geophysical parameters such as woody biomass density will be significantly affected [12], [13]. In an assessment of ionospheric correction requirements for a variety of low-frequency SAR applications, Meyer [14] proposed a more stringent FR correction performance of 1.2 • (maximum standard error) for polarimetry over a general set of ground cover types. An accurate estimate of FR is also required for calibrating the SAR using dedicated calibration targets [15], [16]) FR causes each pixel of the measured four-channel image, M , to deviate from the true backscattering matrix S according to the relation…”

Section: Introductionmentioning

confidence: 99%

“…Biomass technical requirements (see [1, p. 78]) define a threshold NESZ of −27 dB (with a goal of −30 dB) while the crosstalk threshold is −25 dB (with a goal of −30 dB). The values of channel imbalance and crosstalk are likely to vary during the mission and therefore will be estimated in orbit, probably using a combination of polarimetric active radar calibrators and passive reflectors [1], [14], [15], [17]. However, errors in FR estimation during calibration and additive polarimetric noise in the calibrators will cause residual errors in the values of the system calibration terms [15]; these will affect subsequent Biomass measurements.…”

Section: Introductionmentioning

confidence: 99%

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The Accuracy of Faraday Rotation Estimation in Satellite Synthetic Aperture Radar Images

Rogers

Quegan

2014

IEEE Trans. Geosci. Remote Sensing

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Spaceborne linearly polarimetric synthetic aperture radar (SAR) provides information about surface properties and scatterer types by measuring the covariances between images formed using orthogonally polarized radio waves. However, ionospheric Faraday rotation (FR) and system calibration errors alter the balance in the polarimetric channels and distort the covariance matrix. Since FR angles are greater at lower radio frequencies, this paper focuses on the Biomass satellite, which is the European Space Agency's 7th Earth Explorer mission and will carry a P-band (435 MHz) polarimetric SAR. Its primary objective is to measure forest biomass density by combining estimates derived from the polarimetric covariance matrix with estimates based on measuring forest height with polarimetric interferometry and exploiting height-biomass allometric relations. The accuracy of four methods for estimating FR from polarimetric SAR is assessed using simulated images of forest with a range of biomass densities and system errors (H/V channel imbalances, antenna crosstalk, and noise) and over a large spread of FR angles. All methods have biases dependent on the FR, the relative phases of the crosstalk components, and the channel imbalance phase. The best performing method estimates FR to better than 5 • under worst case system errors at all FR angles, so the accuracy of biomass density estimates should not be significantly affected. However, crosstalk phases are predicted to vary greatly across the Biomass antenna beam, and this could potentially cause the FR bias to vary by several degrees across the swath. These effects may occur even for the small values of FR met in L-band data.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Accuracy of Faraday Rotation Estimation in Satellite Synthetic Aperture Radar Images

Rogers

Quegan

2014

IEEE Trans. Geosci. Remote Sensing

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“…The influence of the ionosphere on phase delay tends to be long wavelength (hundreds of km) and, except in the case of L-band data, is commonly ignored. There are, however, several methods for estimating the effect, if necessary (Meyer 2011). Phase delay during propagation through the troposphere, on the other hand, is equally significant at all microwave frequencies and variability is significant over short distances.…”

Section: Atmospheric Phasementioning

confidence: 99%

InSAR and A-InSAR: Theory

Hooper

2014

Encyclopedia of Earthquake Engineering

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“…Moreover, the power of the jamming signals is relatively larger compared to that of the useful signals, and thus the threshold can be easily chosen. Usually, we set η ∈ [2,10]. With classified basis signals, one can find the basis matrix set corresponding to NBI, and the NBI is expressed as…”

Section: A Theory Of Nbi Suppression Using Icamentioning

confidence: 99%

Narrow-Band Interference Suppression for SAR Based on Independent Component Analysis

Zhou

Tao

Bai

et al. 2013

IEEE Trans. Geosci. Remote Sensing

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The narrow-band interference (NBI) is a common jamming signal against synthetic aperture radar (SAR), which can degrade the imaging quality severely. This paper proposes a new method for NBI suppression in the data domain based on the independent component analysis (ICA). In this method, echoes contaminated by the NBI are identified in the frequency domain. Next, time filtering and whitening are performed to the identified echoes. Then, the ICA is carried out to decompose the echoes into a series of basis signals, and the jamming components are selected by thresholding. Finally, the NBI is reconstructed and subtracted from the echoes, and the well-focused SAR imagery is obtained by conventional imaging methods. The proposed method copes well with the time-varying NBI with little signal loss. Results of simulated and measured data have proved the validity of the proposed method.Index Terms-Independent component analysis (ICA), jamming suppression, narrow-band interference (NBI), synthetic aperture radar (SAR).

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Performance Requirements for Ionospheric Correction of Low-Frequency SAR Data

Cited by 108 publications

References 31 publications

The Accuracy of Faraday Rotation Estimation in Satellite Synthetic Aperture Radar Images

The Accuracy of Faraday Rotation Estimation in Satellite Synthetic Aperture Radar Images

InSAR and A-InSAR: Theory

Narrow-Band Interference Suppression for SAR Based on Independent Component Analysis

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