scholarly journals An Improved Clutter Suppression Method for Weather Radars Using Multiple Pulse Repetition Time Technique

2017 ◽  
Vol 2017 ◽  
pp. 1-7 ◽  
Author(s):  
Yingjie Yu ◽  
Yong Li
Keyword(s):  
Time Domain ◽  
Radar Data ◽  
Pulse Repetition ◽  
Estimation Accuracy ◽  
Doppler Velocity ◽  
Clutter Suppression ◽  
Multiple Pulse ◽  
Repetition Time ◽  
Suppression Method ◽  
Velocity Interval

This paper describes the implementation of an improved clutter suppression method for the multiple pulse repetition time (PRT) technique based on simulated radar data. The suppression method is constructed using maximum likelihood methodology in time domain and is called parametric time domain method (PTDM). The procedure relies on the assumption that precipitation and clutter signal spectra follow a Gaussian functional form. The multiple interleaved pulse repetition frequencies (PRFs) that are used in this work are set to four PRFs (952, 833, 667, and 513 Hz). Based on radar simulation, it is shown that the new method can provide accurate retrieval of Doppler velocity even in the case of strong clutter contamination. The obtained velocity is nearly unbiased for all the range of Nyquist velocity interval. Also, the performance of the method is illustrated on simulated radar data for plan position indicator (PPI) scan. Compared with staggered 2-PRT transmission schemes with PTDM, the proposed method presents better estimation accuracy under certain clutter situations.

Evaluation of the Simultaneous Multiple Pulse Repetition Frequency Algorithm for Weather Radar

2008 ◽  
Vol 25 (7) ◽  
pp. 1166-1181 ◽  
Author(s):  
Evan Ruzanski ◽  
John C. Hubbert ◽  
V. Chandrasekar
Keyword(s):  
Pulse Repetition Frequency ◽  
Weather Radar ◽  
Interval Data ◽  
Radar Data ◽  
Repetition Frequency ◽  
Pulse Repetition ◽  
Doppler Velocity ◽  
Mean Power ◽  
Mean Velocity ◽  
Multiple Pulse

Abstract Performance of the simultaneous multiple pulse repetition frequency algorithm (SMPRF) for recovery of mean power and mean Doppler velocity is investigated using simulated weather radar data. Operation and functionality of the algorithm is described; methods to estimate mean power values using statistical inversion and to estimate mean velocity from unevenly spaced autocorrelation function samples are presented and analyzed. A simulation technique for constructing multiple pulse repetition interval data is described and the algorithm performance results are presented for an example SMPRF code using three weather profiles. This leads to the development of an error structure related to factors influencing moment recovery, including finite-length time series effects, the effects of overlaid echoes that create an effective signal-to-noise ratio that limits moment recovery performance, and the effects of spectrum width and radar frequency related to coherence time.

scholarly journals Clutter Suppression for Staggered PRT Waveforms

2008 ◽  
Vol 25 (12) ◽  
pp. 2209-2218 ◽  
Author(s):  
Dmitri N. Moisseev ◽  
Cuong M. Nguyen ◽  
V. Chandrasekar
Keyword(s):  
Time Domain ◽  
State Of The Art ◽  
Radar Signal ◽  
Clutter Suppression ◽  
State University ◽  
Spectral Moments ◽  
Colorado State University ◽  
Current State ◽  
Repetition Time ◽  
State Water

Abstract This paper presents a clutter suppression methodology for staggered pulse repetition time (PRT) observations. It is shown that spectral moments of precipitation echoes can be accurately estimated even in cases where clutter-to-signal ratios are high by using a parametric time domain method (PTDM). Based on radar signal simulations, the accuracy of the proposed method is evaluated for various observation conditions. The performance of PTDM is demonstrated by the implementation of the staggered PRT at the Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL). Based on this study, it is found that the accuracy of the retrieval is comparable to the current state of the art methods applied to the uniformly sampled observations and that the estimated velocity is unbiased for the complete Nyquist range.

Alternating Dual-Pulse, Dual-Frequency Techniques for Range and Velocity Ambiguity Mitigation on Weather Radars

2010 ◽  
Vol 27 (9) ◽  
pp. 1461-1475 ◽  
Author(s):  
Sebastián Torres ◽  
Richard Passarelli ◽  
Alan Siggia ◽  
Pentti Karhunen
Keyword(s):  
Pulse Repetition ◽  
Single Frequency ◽  
Weather Data ◽  
Frequency Diversity ◽  
Sampled Data ◽  
Dual Frequency ◽  
Multiple Pulse ◽  
Uniform Sampling ◽  
Weather Radars ◽  
Repetition Time

Abstract This paper introduces a family of alternating dual-pulse, dual-frequency (ADPDF) techniques. These are based on frequency diversity and are proposed as a means to mitigate range and velocity ambiguities on Doppler weather radars. ADPDF techniques are analyzed theoretically and through simulated and real weather data collected with a prototype C-band radar. Analogous to single-frequency, multiple-pulse-repetition-time (mPRT) techniques, such as staggered or triple PRT, it is demonstrated that ADPDF techniques can extend the maximum unambiguous velocity beyond what is achievable with uniform sampling. However, unlike mPRT techniques, ADPDF techniques exhibit better statistical performance and, more importantly, may be designed to preserve uniform sampling on one of the frequency channels, thus avoiding some of the difficulties associated with processing nonuniformly sampled data.

scholarly journals Constant Raindrop Fall Speed Profiles Derived from Doppler Radar Data Analyses for Steady Nonconvective Precipitation

2005 ◽  
Vol 62 (1) ◽  
pp. 220-230 ◽  
Author(s):  
Robert Nissen ◽  
Roland List ◽  
David Hudak ◽  
Greg M. McFarquhar ◽  
R. Paul Lawson ◽  
...  
Keyword(s):  
Doppler Radar ◽  
Free Fall ◽  
Radar Data ◽  
Measuring System ◽  
Doppler Velocity ◽  
Light Rain ◽  
Fall Speed ◽  
Air Speed ◽  
Velocity Moments ◽  
Rain Rates

Abstract For nonconvective, steady light rain with rain rates <5 mm h−1 the mean Doppler velocity of raindrop spectra was found to be constant below the melting band, when the drop-free fall speed was adjusted for pressure. The Doppler radar–weighted raindrop diameters varied from case to case from 1.5 to 2.5 mm while rain rates changed from 1.2 to 2.9 mm h−1. Significant changes of advected velocity moments were observed over periods of 4 min. These findings were corroborated by three independent systems: a Doppler radar for establishing vertical air speed and mean terminal drop speeds [using extended Velocity Azimuth Display (EVAD) analyses], a Joss–Waldvogel disdrometer at the ground, and a Particle Measuring System (PMS) 2-DP probe flown on an aircraft. These measurements were supported by data from upper-air soundings. The reason why inferred raindrop spectra do not change with height is the negligible interaction rate between raindrops at low rain rates. At low rain rates, numerical box models of drop collisions strongly support this interpretation. It was found that increasing characteristic drop diameters are correlated with increasing rain rates.

scholarly journals Gaussian Model Adaptive Processing in Time Domain (GMAP-TD) for Weather Radars

2013 ◽  
Vol 30 (11) ◽  
pp. 2571-2584 ◽  
Author(s):  
Cuong M. Nguyen ◽  
V. Chandrasekar
Keyword(s):  
Time Domain ◽  
Gaussian Model ◽  
Radar Data ◽  
Adaptive Processing ◽  
Colorado State University ◽  
Weather Radars ◽  
Ground Clutter ◽  
Moment Estimation ◽  
Interpolation Procedure ◽  
The Time Domain

Abstract The Gaussian model adaptive processing in the time domain (GMAP-TD) method for ground clutter suppression and signal spectral moment estimation for weather radars is presented. The technique transforms the clutter component of a weather radar return signal to noise. Additionally, an interpolation procedure has been developed to recover the portion of weather echoes that overlap clutter. It is shown that GMAP-TD improves the performance over the GMAP algorithm that operates in the frequency domain using both signal simulations and experimental observations. Furthermore, GMAP-TD can be directly extended for use with a staggered pulse repetition time (PRT) waveform. A detailed evaluation of GMAP-TD performance and comparison against the GMAP are done using simulated radar data and observations from the Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) radar using uniform and staggered PRT waveform schemes.

Rain drop size distributions estimated from NOAA Snow-Level Radar data

2021 ◽  
Keyword(s):  
Drop Size ◽  
Radar Data ◽  
Limited Range ◽  
Doppler Velocity ◽  
Velocity Spectrum ◽  
A Value ◽  
Rain Drop ◽  
Prior Literature ◽  
Air Motion ◽  
Drop Size Distributions

Abstract Using NOAA’s S-band High Power Snow-Level Radar, HPSLR, a technique for estimating the rain drop size distribution (DSD) above the radar is presented. This technique assumes the DSD can be described by a four parameter, generalized Gamma distribution (GGD). Using the radar’s measured average Doppler velocity spectrum and a value (assumed, measured, or estimated) of the vertical air motion, w, an estimate of the GGD is obtained. Four different methods can be used to obtain w. One method that estimates a mean mass-weighted raindrop diameter, Dm, from the measured reflectivity, Z, produces realistic DSDs compared to prior literature examples. These estimated DSDs provide evidence that the radar can retrieve the smaller drop sizes constituting the “drizzle” mode part of the DSD. This estimation technique was applied to 19 h of observations from Hankins, NC. Results support the concept that DSDs can be modeled using GGDs with a limited range of parameters. Further work is needed to validate the described technique for estimating DSDs in more varied precipitation types and to verify the vertical air motion estimates.

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