RFI Detection and Mitigation for Advanced Correlators in Interferometric Radiometers

Abstract

This work presents the first RFI detection and mitigation algorithm for the interferometric radiometers that will be implemented in its correlator unit. The algorithm operates in the time and frequency domains, applying polarimetric and statistical tests in both domains, and exhibiting a tunable and arbitrary low probability of false alarm. It is scalable to a configurable number of receivers, and it is optimized in terms of quantization bits and the implementation of the cross-correlations in the time or frequency domains for hardware resource saving. New features of this algorithm are the computation of the Stokes parameters per frequency bin in the Short-Time Fourier Transform and a new parameter called Polarimetric Kurtosis. If RFI is detected in one domain or in both, it is removed using the calculated blanking masks. The optimum algorithm parameters are computed, such as length of the FFTs, the threshold selection for a given probability of false alarm, and the selection of the blanking masks. Last, an important result refers to the application of Parseval’s theorem for the computation of the cross-correlations in the frequency domain, instead of in the time domain, which is more efficient and leads to smaller errors even when using moderate quantization levels. The algorithm has been developed in the framework of the ESA’s technology preparation for a potential L-band radiometer mission beyond SMOS. However, it is also applicable to (polarimetric) real aperture radiometers, and its performance would improve if more than one bit is used in the signal quantization.

Development of a Dynamically Re-Configurable Radio-Frequency Interference Detection System for L-Band Microwave Radiometers

“…For this reason, when detecting RFI and flagging data as corrupted, it is beneficial to do so in bandwidths that are a fraction of the 1400-1427 MHz frequency range. A typical solution to this segmented analysis of signals is known as a filter bank [7,9]. A filter bank refers to a set of filters that are used to separate and process signals within different frequency bands.…”

“…The window used in the implementation is a square-root Hamming window, defined as in Equation ( 1) [9]. To apply the window, the data must be read non-sequentially to obtain the overlap, compared to the arrival order.…”

“…However, in practice, as thermal noise is zero-mean, non-central moments are equivalent and used for the calculation of the kurtosis. Depending on the characteristics of the receiver, the detection of RFI can be approached from different angles (i.e., depending on the quantization [8,9] or computational requirements [10]). Data acquisition and processing for microwave radiometers is usually implemented using a combination of a Radio Frequency (RF) front-end, typically a Software-Defined Radio (SDR), and a Field-Programmable Gate Array (FPGA) board, which allows for a modular approach regarding the reception chain and the Digital Signal Processing (DSP) stages.…”

TriHex: Combining Formation Flying, General Circular Orbits, and Alias-Free Imaging, for High-Resolution L-Band Aperture Synthesis

“…The technology of TriHex is mostly based on the one used in SMOS, improved through technology activities ESA is, or has been, carrying out [33]: a 0.577λ envelope antenna [24], a dualfrequency advanced receiver [22] including a new RF ASIC [34], a multi-wavelength optical harness [35] and an advanced correlator unit with the built-in capability of filtering out Radio Frequency Interference [36].…”