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RFI mitigation for UWB radar via SPICE
Author(s): Jeremy Johnston; Jiaying Ren; Tianyi Zhang; Jian Li; Lam Nguyen
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Paper Abstract

It is well-known that ultra-wideband (UWB) radar suffers substantial disturbances due to spectral overlap with common radio frequency interferers (RFI), such as commercial radio/TV broadcasts, cell phones, and ISM equipment. We can expect RFI to become more prevalent as the cost of the technology decreases and devices become more widely commercialized. Fortunately, the energy of typical RFI is concentrated in narrow frequency bands – i.e. sparse in the frequency domain – which lends the RFI removal task to a sparsity-driven estimation approach. Moreover, the radar echoes tend to be sparse in the time domain. The recent SParse Iterative Covariance-based Estimation (SPICE) algorithm is employed to exploit these properties for effective RFI mitigation. We compare the performance of SPICE with that of the robust principal component analysis (RPCA) in a simulated interference environment consisting of an actual ambient RFI recording scaled and added to an unadulterated radar signal. SPICE is a user-parameter free algorithm, making it easy to use in practical applications such as RFI mitigation; while, in contrast, RPCA requires a tuning parameter, whose optimal value was found to depend on the signal-to-interference ratio of the contaminated data. Moreover, SPICE is computationally more efficient than RPCA.

Paper Details

Date Published: 4 May 2018
PDF: 9 pages
Proc. SPIE 10633, Radar Sensor Technology XXII, 106330D (4 May 2018); doi: 10.1117/12.2301363
Show Author Affiliations
Jeremy Johnston, Univ. of Florida (United States)
Jiaying Ren, Univ. of Florida (United States)
Tianyi Zhang, Univ. of Florida (United States)
Jian Li, Univ. of Florida (United States)
Lam Nguyen, U.S. Army Research Lab. (United States)


Published in SPIE Proceedings Vol. 10633:
Radar Sensor Technology XXII
Kenneth I. Ranney; Armin Doerry, Editor(s)

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