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Multi-PRI signal processing for the terminal Doppler weather radar, part I: clutter filtering

May 1, 2005
  |
Journal Article
Author:
John Y. Cho
…
Published in:
J. Atmos. Ocean. Technol., Vol. 22, May 2005, pp. 575-582.
Topic:
algorithms
R&D area:
R&D group:

Summary

Multiple pulse repetition interval (multi-PRI) transmission is part of an adaptive signal transmission and processing algorithm being developed to aggressively combat range-velocity ambiguity in weather radars. In the past, operational use of multi-PRI pulse trains has been hampered due to the difficulty in clutter filtering. This paper presents finite impulse response clutter filter designs for multi-PRI signals with excellent magnitude and phase responses. These filters provide strong suppression for use on low-elevation scans and yield low biases of velocity estimates so that accurate velocity dealiasing is possible. Specifically, the filters are designed for use in the Terminal Doppler Weather Radar (TDWR) and are shown to meet base data bias requirements equivalent to the Federal Aviation Administration's specifications for the current TDWR clutter filters. Also an adaptive filter selection algorithm is proposed that bases its decision on clutter power estimated during an initial long-PRI surveillance scan. Simulations show that this adaptive algorithm yields satisfactory biases for reflectivity, velocity, and spectral width. Implementation of such a scheme would enable automatic elimination of anomalous propagation signals and constant adjustment to evolving ground clutter conditions, an improvement over the current TDWR clutter filtering system.
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Summary

Multiple pulse repetition interval (multi-PRI) transmission is part of an adaptive signal transmission and processing algorithm being developed to aggressively combat range-velocity ambiguity in weather radars. In the past, operational use of multi-PRI pulse trains has been hampered due to the difficulty in clutter filtering. This paper presents finite impulse...

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Multi-PRI signal processing for the terminal Doppler weather radar, part I: clutter filtering

Automated storm tracking for terminal air traffic control

September 1, 1995
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Journal Article
Author:
Edward S. Chornoboy
…
Published in:
Lincoln Laboratory Journal, Vol. 7, No. 2, Fall 1994, pp. 427-448.
Topic:
air traffic control
R&D area:
R&D group:

Summary

Good estimates of storm motion are essential to improved air traffic control operations during times of inclement weather. Automating such a service is a challenge, however, because meteorological phenomena exist as complex distributed systems that exhibit motion across a wide spectrum of scales. Even when viewed from a fixed perspective, these evolving dynamic systems can test the extent of our definition of motion, as well as any attempt at automated tracking of this motion. Image-based motion detection and processing appear to provide the best route toward robust performance of an automated tracking system.
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Summary

Good estimates of storm motion are essential to improved air traffic control operations during times of inclement weather. Automating such a service is a challenge, however, because meteorological phenomena exist as complex distributed systems that exhibit motion across a wide spectrum of scales. Even when viewed from a fixed perspective...

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Automated storm tracking for terminal air traffic control

Data processing techniques for airport surveillance radar weather sensing

May 8, 1995
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Conference Paper
Author:
Mark E. Weber
…
Published in:
Proc. IEEE 1995 Int. Radar Conf., 8-11 May 1995, pp. 521-528.
Topic:
aviation weather
R&D area:
R&D group:

Summary

Discusses data processing techniques that can provide high quality, automated weather information using the FAA's existing Airport Surveillance Radars (ASR-9). The cost of modifying the ASR-9 is significantly less than that for deployment of the dedicated terminal Doppler weather radar. These techniques have been implemented on a prototype ASR-9 weather surveillance processor (WSP) and have been tested operationally at the Orlando, FL and Albuquerque, NM air traffic control towers. The key to the success of this system has been the development of innovative data processing techniques that accommodate the non-optimum parameters of the ASR as a weather sensor. The authors motivate the development of the ASR-9 WSP system and describe in detail the data processing techniques that have been employed to achieve an operationally useful capability. They provide an overview of the WSP and the ongoing system development and test program. They provide specifics on the data processing algorithms that have been key to successful implementation of this capability.
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Summary

Discusses data processing techniques that can provide high quality, automated weather information using the FAA's existing Airport Surveillance Radars (ASR-9). The cost of modifying the ASR-9 is significantly less than that for deployment of the dedicated terminal Doppler weather radar. These techniques have been implemented on a prototype ASR-9 weather...

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Data processing techniques for airport surveillance radar weather sensing

Optimum time-varying FIR filter designs for the Airport Surveillance Radar wind shear processor

December 28, 1994
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Project Report
Author:
Edward S. Chornoboy
Published in:
MIT Lincoln Laboratory Report ATC-191
Topic:
wind shear
R&D area:
R&D group:

Summary

We have developed new design algorithms for finite impulse response (FIR) filters that compensate for arbitrary input spacing and that allow for arbitrary group delay specification. The potential of these new designs to work with the ASR-9 staggered pulse spacing is examined in the context of the ASR-9 wind-shear processor (WSP). Benefits derived from the new designs include an improved (optimal) stopband design, an increased yield in pulse samples for moments estimation, and the retention of pulse-stagger phase information, which can be used for velocity dealiasing. These improvements are demonstrated using simulated and test-bed data, the latter acquired during 1991/1992 Orlando operations. Filter utilization, in the context of a pre-existing adaptive selection scheme (1) and the Orlando (FL) clutter environment, is examined using the new filters, and areas for improvement are identified.
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Summary

We have developed new design algorithms for finite impulse response (FIR) filters that compensate for arbitrary input spacing and that allow for arbitrary group delay specification. The potential of these new designs to work with the ASR-9 staggered pulse spacing is examined in the context of the ASR-9 wind-shear processor...

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Optimum time-varying FIR filter designs for the Airport Surveillance Radar wind shear processor

Variable-PRI processing for meteorologic Doppler radars

March 29, 1994
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Conference Paper
Author:
Edward S. Chornoboy
…
Published in:
1994 IEEE Natl. Radar Conf., 29-31 March 1994, pp. 85-90.
Topic:
doppler radar
R&D area:
R&D group:

Summary

In this communication we described how, with nonuniform sampling, the concept of bandlimited extrapolation can be used to obtain unambiguous Doppler velocity estimates in the supra-Nyquist region. The proposed method coherently processes a multi-PRI sample using a generalized form of periodogram analysis. The work is described in the context of meteorologic Doppler processing and includes a discussion of effective suppression for stationary ground clutter when multi-PRI schemes are used.
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Summary

In this communication we described how, with nonuniform sampling, the concept of bandlimited extrapolation can be used to obtain unambiguous Doppler velocity estimates in the supra-Nyquist region. The proposed method coherently processes a multi-PRI sample using a generalized form of periodogram analysis. The work is described in the context of...

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Variable-PRI processing for meteorologic Doppler radars

Extrapolating storm location using the Integrated Terminal Weather System (ITWS) storm motion algorithm

March 29, 1994
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Project Report
Author:
Edward S. Chornoboy
…
Published in:
MIT Lincoln Laboratory Report ATC-208
Topic:
weather
R&D area:
R&D group:

Summary

Storm Motion (SM) is a planned Initial Operational Capability (IOC) algorithm of the FAA's Integrated Terminal Weather System (ITWS). As currently designed, this algorithm will track the movement of storms/cells and convey this tracking information to the ITWS user by means of a graphic display of vectors (for direction) with accompanying numeric reports of storm speed, rounded to the nearest 5 nmi/hr increment. Recognizing that there are occasions when ITWS users could benefit from a more extended product format, Storm Extrapolated Position (SEP) was conceived to supplement the SM product and thereby increase the latter's accessibility as a planning aid. This communication describes a prototype SEP design along with an analysis of its accuracy and observed performance during 1993 ITWS demnstrations in Orlando (FL) and Dallas (TX).
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Summary

Storm Motion (SM) is a planned Initial Operational Capability (IOC) algorithm of the FAA's Integrated Terminal Weather System (ITWS). As currently designed, this algorithm will track the movement of storms/cells and convey this tracking information to the ITWS user by means of a graphic display of vectors (for direction) with...

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Extrapolating storm location using the Integrated Terminal Weather System (ITWS) storm motion algorithm

Clutter filter design for multiple-PRT signals

May 24, 1993
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Conference Paper
Author:
Edward S. Chornoboy
Published in:
Proc. 26th Int. Conf. on Radar Meteorology, 24-28 May 1993, pp. 235-237.
Topic:
weather
R&D area:
R&D group:

Summary

The trade-off of range vs. velocity ambiguity is fundamental and operationally significant for many S- and C-band pulsed Doppler weather radars. Transmission schemes using multiple pulse repetition times (PRTs) (i.e., nonuniform pulse spacing) offer the potential for extending the unambiguous measurement range by resolving intervals of velocity ambiguity. Unfortunately, multiple PRT methods can be problematic with low-elevation scanning when ground clutter removal is required. We have constructed both Chebyshev and mean-squared error (MSE) desing algorithms (Choroboy, 1993) that deal with design in the complex domain; the MSE algorithms are described below.
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Summary

The trade-off of range vs. velocity ambiguity is fundamental and operationally significant for many S- and C-band pulsed Doppler weather radars. Transmission schemes using multiple pulse repetition times (PRTs) (i.e., nonuniform pulse spacing) offer the potential for extending the unambiguous measurement range by resolving intervals of velocity ambiguity. Unfortunately, multiple...

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Clutter filter design for multiple-PRT signals

Coherent processing across multi-PRI waveforms

May 24, 1993
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Conference Paper
Author:
Mark E. Weber
…
Published in:
Proc. 26th Int. Conf. on Radar Meteorology, 24-28 May 1993, pp. 232-234.
Topic:
doppler radar
R&D area:
R&D group:

Summary

Meteorological Doppler radars have typically utilized constant pulse-repetition intervals (PRI) to facilitate clutter filtering and estimation of weather echo spectral moments via pulse-pair or periodogram-based algorithms. Utilization of variable PRIs to support resolution of velocity ambiguities has been discussed, for example by Banjanin and Zrnic, but not implemented owing to difficulties associated with clutter filter design. Recent work by Chornoboy presents design algorithms for time-varying finite impulse response (FIR) filters that achieve Chebyshev or mean-squared error (MSE) optimality when processing multi-PRI waveforms. This paper is a follow-on to that work, treating techniques for post-clutter filter processing (e.g. periodogram estimation) that are appropriate for such waveforms. Our approach involves a least-squares fitting of the signal - sampled at a nonuniform rate - to a weighted sum of uniformly spaces sinusoids. The sinusoids or "basis functions" are chosen to span a Nyquist interval consistent with the longest PRI in the transmitted waveform, and need not be centered at zero Doppler. Determination of the sinusoid weightings - effectively a discrete Fourier transformation (DFT) - and the associated residual between the harmonic fit and the data area accomplished via multiplications of the signal vector with precomputed matrices. The resulting spectrum estimate can be used directly for weather echo moment calculations, or can be inverse-Fourier transformed using conventional techniques to generate a time-domain signal representation. This work has been motivated by a specific application - estimation of weather spectrum moments for a Wind Shear Processor (WSP) modification to the Federal Aviation Administration's Airport Surveillance Radar (ASR-9). Our approach supports candidate low-altitude radial wind estimation algorithms that operate on frequency-domain signal representations and require that the radar's block-stagger PRI and the possibility of velocity ambiguities be accounted for in generating the spectrum estimates. In principle, however, these processing techniques are also applicable to weather radar systems such as WSR-88D and Terminal Doppler Weather Radar (TDWR) where range and Doppler ambiguities are an operational concern.
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Summary

Meteorological Doppler radars have typically utilized constant pulse-repetition intervals (PRI) to facilitate clutter filtering and estimation of weather echo spectral moments via pulse-pair or periodogram-based algorithms. Utilization of variable PRIs to support resolution of velocity ambiguities has been discussed, for example by Banjanin and Zrnic, but not implemented owing to...

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Coherent processing across multi-PRI waveforms

Optimal mean velocity estimation for Doppler weather radars

May 1, 1993
  |
Journal Article
Author:
Edward S. Chornoboy
Published in:
IEEE Trans. Geosci. Remote Sens., Vol. 31, No. 3, May 1993, pp. 575-586.
Topic:
remote sensing
R&D area:
R&D group:

Summary

Optimal Doppler velocity estimation is explored for a standard Gaussian signal measurement model and thematic maximum likelihood (ML) and Bayes estimation. Because the model considered depends on a vector parameter (velocity, spectrum width (SW), and signal-to-noise ratio (SNR), the exact formulation of an ML or Bayes solution involves a system of coupled equations which cannot be made explicit for any of the parameters. In the past, iterative methods have been suggested for solving the required equations. In addition to being computationally intensive, it is unclear whether an iterative method can be constructed to converge well under general conditions. Simple computational forms are shown to exist when SW and SNR are assumed known. An information theoretic concept is used to propose an adaptive extension of these equations to the general case of SW and SNR unknown. This new idea is developed to the poise of operational application. A Monte Carlo simulations experiment is used to verify that the method can work; the example presented considers the particularly difficult situation of no a priori information for either SW or SNR under the additional constraint of a very small (20 pulse samples) sample size. The improved performance of this new Doppler velocity estimator is documented by comparison with derived optimal bounds and with the performance of the well-known pulse pair (PP) method. Small-sample estimator statistics are presented; and Bayes estimator results, assuming known SW and SNR, are used to provide true performance bounds for comparison. Cramer-Rao (CR) bounds are also derived and shown to be inferior to the Bayes bounds in the small sample case considered.
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Summary

Optimal Doppler velocity estimation is explored for a standard Gaussian signal measurement model and thematic maximum likelihood (ML) and Bayes estimation. Because the model considered depends on a vector parameter (velocity, spectrum width (SW), and signal-to-noise ratio (SNR), the exact formulation of an ML or Bayes solution involves a system...

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Optimal mean velocity estimation for Doppler weather radars

Storm tracking for TDWR: a correlation algorithm design and evaluation

July 14, 1992
  |
Project Report
Author:
Edward S. Chornoboy
Published in:
MIT Lincoln Laboratory Report ATC-182
Topic:
algorithms
R&D area:
R&D group:

Summary

Storm Movement Prediction (SMP) is a proposed (future) product for Terminal Doppler Weather Radar (TDWR), aiding controllers by tracking storms approaching and passing through the terminal environment. Because the scan strategy (data acquisition) of TDWR has been critically designed to meet the needs of its primary function, which is the detection of hazardous low-altitude wind shear, there is the question of whether reliable storm tracking can be obtained from the TDWR data set. The objectives of storm tracking involve a scope (spatial range) much larger than that required for the wind-shear algorithms where volume coverage is confined (in off-airport sited radars) to a sector covering the important approach and departure corridors and the only 360-degree scans are near-surface scans for gust-front detection. This report examines the application of a correlation based method of detecting storm motion, testing the notion that reliable storm motion can be inferred from existing TDWR data. In particular, storm motion derived from an analysis of the TDWR Precipitation product (PCP) is studied. A summary description of the algorithm is presented along with an analysis of its performance using data from MIT Lincoln Laboratory's TDWR testbed operations in Denver (1988) and Kansas City (1989). The primary focus of the present analysis is on the reliability of tracking, since the algorithm is expected to operate in an autonomous environment. Some attention is given to the idea of prediction, in the form of storm extrapolation, considering 15, 30, and 60 minute predictions. Specific areas for improvement are identified, and application of hte algorithm track vectors for long-term prediction (30-60 minutes) is discussed with reference to example PCP images.
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Summary

Storm Movement Prediction (SMP) is a proposed (future) product for Terminal Doppler Weather Radar (TDWR), aiding controllers by tracking storms approaching and passing through the terminal environment. Because the scan strategy (data acquisition) of TDWR has been critically designed to meet the needs of its primary function, which is the...

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Storm tracking for TDWR: a correlation algorithm design and evaluation
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