Colorado State University Research Foundation

Cuong M Nguyen

Chandrasekaran Venkatachalam

Nitin Bharadwaj

Dmitri N Moisseev

Dmitriy Moiseev

Embodiments of the present invention provide for improved estimation of environmental parameters in a dual-polarization radar system. In some embodiments, environmental parameters can be estimated using a linear combination of data received in two orthogonal polarization states. In particular, embodiments of the invention improve ground clutter and noise mitigation in dual polarization radar systems. Moreover, embodiments of the invention also provide for systems to determine the differential reflectivity and/or the magnitude of the co-polar correlation coefficient and the differential phase in a dual polarization radar system.

Dual-polarization radar processing system using time domain method

Sensitivity is a critical aspect of weather radar systems. Such systems not only detect atmospheric patterns but often need to precisely measure weak precipitation echoes. Embodiments of the invention use pulse compression techniques to increase the sensitivity of weather radar systems. These techniques can include sending two waveforms into a region of interest, where the second waveform is designed based on knowledge about the first waveform. Such systems can enhance the sensitivity of weather radars about 10 dB.

Sensitivity enhancement system

Embodiments of the present invention provide a Gaussian adaptive filter for ground clutter filtering and signal parameter estimation for weather radars in the time domain. In some embodiments, the filtering can be applied to dual polarization radar systems. In some embodiments, the clutter component of the signal can be transformed to noise. An interpolation procedure can then be used to recover the transformed part of the weather. A unique filter can be designed to use for both H and V channels for dual-polarization parameter estimation. In addition, the filter can be directly extended for staggered PRT 2/3 sampling scheme.

Gaussian model adaptive processing in the time domain

Methods and systems are disclosed for investigating a region of interest with a radar. A radar signal is propagated to the region of interest. Sampled time-domain radar data scattered within the region of interest are collected. A likelihood function is calculated with the sampled time-domain data within a parametric model of the region of interest for a defined set of parameters. The set of parameters in varied to find an extremum of the likelihood function.

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Fort Collins, CO, United States of America

Cuong M Nguyen