Ionospheric Distortions of P-band Radar

Introduction

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The ESA BIOMASS mission, planned for launch in the coming years, is a landmark Earth observation mission aimed at quantifying the world’s forest above-ground biomass (AGB) using spaceborne P-band synthetic aperture radar (SAR). This mission is designed to address significant knowledge gaps in our understanding of the global carbon cycle by providing accurate and consistent data on biomass distribution. The data collected by BIOMASS will contribute to improved climate change models, more informed policy-making, and effective mitigation strategies.

Operating at P-band frequencies (~435 MHz), the radar system on BIOMASS can penetrate dense vegetation layers, enabling it to gather detailed information about forest structure, biomass, and changes over time. However, a key technical challenge associated with this low-frequency radar operation is its increased sensitivity to ionospheric distortions. These distortions, if left uncorrected, can significantly degrade the quality of SAR images and impact the accuracy of biomass estimation products generated by the mission. Understanding and mitigating these effects is therefore critical to ensuring the success of BIOMASS.

The Ionosphere and Its Effects on P-band Radar

The ionosphere is a plasma-rich region of Earth’s upper atmosphere that extends from roughly 60 km to over 1,000 km in altitude. It contains free electrons and ions that interact with electromagnetic waves traveling through it. This interaction varies depending on several factors, including solar activity, geographic location, local time, and seasonal variations. For radar signals operating at lower frequencies, like the P-band, the ionosphere poses a range of challenges that can significantly affect SAR data quality.

1. Faraday Rotation

Faraday rotation is one of the most prominent ionospheric effects on P-band radar signals. As a linearly polarized radar wave traverses the ionosphere, its polarization plane rotates due to the presence of the Earth’s magnetic field and free electrons. The magnitude of this rotation is directly related to the Total Electron Content (TEC) along the radar signal path and the frequency of the radar signal itself. At P-band frequencies, the Faraday rotation angle can be substantial, sometimes exceeding tens of degrees. If not corrected, this effect can distort polarimetric SAR (PolSAR) data, leading to inaccuracies in the interpretation of scattering mechanisms and errors in algorithms that estimate forest biomass from polarimetric observables.

2. Group Delay and Phase Advance

Group delay refers to the additional time it takes for the radar signal to propagate through the ionosphere due to the dispersion introduced by free electrons. Similarly, phase advance describes the shifting of the radar signal phase, which can introduce significant errors in phase measurements used in InSAR (Interferometric SAR) applications. Variations in TEC between two SAR acquisitions can result in differential phase delays, producing long-wavelength phase ramps in interferograms. These artifacts can reduce coherence, complicate phase unwrapping, and undermine the reliability of PolInSAR-derived forest height and structure products.

3. Scintillation

Scintillation refers to rapid, random fluctuations in the amplitude and phase of the radar signal caused by small-scale irregularities in the ionosphere’s electron density. Scintillation effects are more prevalent at equatorial and polar latitudes and during periods of high solar activity. These fluctuations can increase the noise floor of SAR images, reduce signal-to-noise ratio (SNR), and impair the quality of both polarimetric and interferometric measurements.

Impact on the ESA BIOMASS Mission

The BIOMASS satellite will operate in a dawn-dusk sun-synchronous orbit at approximately 660 km altitude. This orbit ensures global coverage, including regions most critical for biomass monitoring, such as the tropical rainforests of the Amazon Basin, Central Africa, and Southeast Asia. However, these equatorial regions are also characterized by elevated ionospheric activity, particularly in terms of high TEC values and frequent scintillation events.

The impact of ionospheric disturbances on the BIOMASS mission includes:

• Polarimetric Data Distortion: Faraday rotation can compromise the fidelity of polarimetric measurements by altering the polarization state of the backscattered signals. This can affect the performance of polarimetric decompositions and classification algorithms used to estimate forest type, density, and biomass.
• Interferometric Phase Errors: Variations in TEC between different acquisition times can introduce significant phase delays, leading to reduced coherence in repeat-pass InSAR and PolInSAR processing. This reduces the accuracy of forest height measurements and hampers the extraction of vertical vegetation structure information.
• Geolocation Errors: Group delay effects can cause systematic shifts in the SAR image’s range and azimuth directions, degrading geolocation accuracy. Such errors complicate multi-temporal analyses, mosaicking of large areas, and data fusion with optical or LiDAR datasets.

Mitigation Strategies

Recognizing the risks posed by ionospheric distortions, ESA has developed a comprehensive set of mitigation strategies to ensure the quality and reliability of BIOMASS data products.

1. Faraday Rotation Estimation and Correction

The fully polarimetric design of BIOMASS SAR allows for the estimation of Faraday rotation angles directly from the measured data. Algorithms based on polarimetric calibration matrices and rotation vector analysis are employed to compute and correct the Faraday rotation in each pixel. Correcting Faraday rotation restores the physical meaning of polarimetric observables, enabling accurate biomass retrieval using decomposition techniques like the Cloude-Pottier and Freeman-Durden models.

2. Use of External TEC Data

BIOMASS leverages external TEC measurements from GNSS receivers onboard satellites and ground-based stations. Additionally, global ionospheric models such as IRI (International Reference Ionosphere) and NeQuick provide spatially and temporally resolved TEC estimates. These data sources are integrated into the SAR processing chain to correct for group delays and phase advances, improving interferometric phase stability and geolocation accuracy.

3. Cross-Polarization Channels

The cross-polarized HV or VH channels in BIOMASS SAR are less sensitive to Faraday rotation effects because the rotation-induced changes are more predictable. These channels serve as important references for validating Faraday correction algorithms and can provide more robust inputs for polarimetric classification in heavily disturbed ionospheric conditions.

4. Temporal and Spatial Filtering

To mitigate the impact of scintillation and other high-frequency noise, BIOMASS employs multi-looking to increase SNR at the expense of spatial resolution. Temporal averaging across multiple acquisitions and advanced spatial filtering techniques further enhance the quality of interferometric products. The mission also plans to avoid acquisitions during predicted periods of ionospheric storms or extreme solar activity.

5. Calibration and Validation (Cal/Val) Campaigns

A cornerstone of BIOMASS’s strategy is its extensive Cal/Val program, which involves deploying corner reflectors, coherent transponders, and GNSS TEC monitors at key calibration sites. These ground-based assets help verify the performance of ionospheric correction algorithms and ensure the accuracy of delivered SAR data products. Regular calibration campaigns provide essential feedback for refining the correction models and algorithms over the mission lifetime.

Scientific and Operational Significance

Accurate correction of ionospheric distortions is essential for BIOMASS to deliver on its primary scientific objectives. Reliable estimates of above-ground biomass will reduce uncertainties in global carbon stock assessments and contribute valuable data for climate change models, REDD+ reporting, and forest management strategies.

Moreover, BIOMASS will provide critical insights into forest dynamics, including rates of deforestation, degradation, and forest recovery, particularly in tropical regions. The mission’s success will also establish best practices for future P-band SAR missions, including those designed for geohazard monitoring, ice sheet dynamics, and subsurface imaging.

Conclusion

The ionosphere presents significant challenges for low-frequency radar missions like ESA’s BIOMASS, but through a combination of polarimetric calibration, external TEC data integration, advanced filtering, and calibration/validation campaigns, ESA is well-prepared to mitigate these effects. By addressing ionospheric distortions comprehensively, BIOMASS is poised to provide accurate, high-quality data that will enhance our understanding of the world’s forests and support global efforts to combat climate change.

Expand Your Knowledge – Dive Deeper

• The ESA BIOMASS mission in EO-College

Further Reading

• Rogers, N. C., Quegan, S., Kim, J. S., & Papathanassiou, K. P. (2013). Impacts of ionospheric scintillation on the BIOMASS P-band satellite SAR. IEEE Transactions on Geoscience and Remote Sensing, 52(3), 1856-1868.
• Rogers, N., & Quegan, S. (2013, April). Faraday rotation correction for the ESA BIOMASS P-band synthetic aperture radar. In 2013 7th European Conference on Antennas and Propagation (EuCAP) (pp. 3919-3923). IEEE.
• Quegan, S., Chave, J., Dall, J., Le Toan, T., Papathanassiou, K., Rocca, F., … & Williams, M. (2012, July). The science and measurement concepts underlying the BIOMASS mission. In 2012 IEEE International Geoscience and Remote Sensing Symposium (pp. 5542-5545). IEEE.