Coherent Doppler Lidar for Wind Sensing

An eye-safe all-fiber Coherent Doppler Lidar for wind sensing system has been developed and tested at the Remote Sensing Laboratory of the City College of New York, New York, NY. The system, which operates at a 20 kHz pulse repetition rate and acquires lidar return signals at 400 MSample/s, accumulates signals that are as much as 20 dB lower than the receiver noise power by using embedded programming techniques. Two FPGA embedded programming algorithms are designed and compared. In the first algorithm, power spectra of return signals are calculated and accumulated for different range gates. Line of sight wind speed estimates can then be calculated after transferring the range gated accumulated power spectra to a host computer. In the second FPGA algorithm, a digital IQ demodulator and down sampler allow an autocorrelation matrix representing a pre-selected number of lags to be accumulated. Precision in the velocity measurements is estimated to be on the order of 0.08 m/s and the precision in the measured horizontal wind direction is estimated to be to be about 2°

A satellite-based radar wind sensor

The objective is to investigate the application of Doppler radar systems for global wind measurement. A model of the satellite-based radar wind sounder (RAWS) is discussed, and many critical problems in the designing process, such as the antenna scan pattern, tracking the Doppler shift caused by satellite motion, and backscattering of radar signals from different types of clouds, are discussed along with their computer simulations. In addition, algorithms for measuring mean frequency of radar echoes, such as the Fast Fourier Transform (FFT) estimator, the covariance estimator, and the estimators based on autoregressive models, are discussed. Monte Carlo computer simulations were used to compare the performance of these algorithms. Anti-alias methods are discussed for the FFT and the autoregressive methods. Several algorithms for reducing radar ambiguity were studied, such as random phase coding methods and staggered pulse repitition frequncy (PRF) methods. Computer simulations showed that these methods are not applicable to the RAWS because of the broad spectral widths of the radar echoes from clouds. A waveform modulation method using the concept of spread spectrum and correlation detection was developed to solve the radar ambiguity. Radar ambiguity functions were used to analyze the effective signal-to-noise ratios for the waveform modulation method. The results showed that, with suitable bandwidth product and modulation of the waveform, this method can achieve the desired maximum range and maximum frequency of the radar system

Designing clutter rejection filters with complex coefficients for airborne pulsed Doppler weather radar

Ground clutter interference is a major problem for airborne pulse Doppler radar operating at low altitudes in a look-down mode. With Doppler zero set at the aircraft ground speed, ground clutter rejection filtering is typically accomplished using a high-pass filter with real valued coefficients and a stopband notch centered at zero Doppler. Clutter spectra from the NASA Wind Shear Flight Experiments of l991-1992 show that the dominant clutter mode can be located away from zero Doppler, particularly at short ranges dominated by sidelobe returns. Use of digital notch filters with complex valued coefficients so that the stopband notch can be located at any Doppler frequency is investigated. Several clutter mode tracking algorithms are considered to estimate the Doppler frequency location of the dominant clutter mode. From the examination of night data, when a dominant clutter mode away from zero Doppler is present, complex filtering is able to significantly increase clutter rejection over use of a notch filter centered at zero Doppler

Middle Atmosphere Program. Handbook for MAP. Volume 13: Ground-based Techniques

Topics of activities in the middle Atmosphere program covered include: lidar systems of aerosol studies; mesosphere temperature; upper atmosphere temperatures and winds; D region electron densities; nitrogen oxides; atmospheric composition and structure; and optical sounding of ozone

Improved SuperDARN radar signal processing: A first principles statistical approach for reliable measurement uncertainties and enhanced data products

Ground-based radar systems are the best way to continuously monitor medium-to-large-scale features of the near-Earth space environment on a global scale. The Super Dual Auroral Radar Network (SuperDARN) radars are used to image the high-latitude ionospheric plasma circulation, which is produced by magnetosphere-ionosphere coupling processes generated by the interaction of both the solar and terrestrial magnetic fields. While investigating ways to expand the usable data products of SuperDARN to include electron density inferred using a multiple-frequency technique, it was determined that SuperDARN error estimates were lacking sufficient rigour. The method to calculate SuperDARN parameters was developed approximately 25 years ago when available computing resources were significantly less powerful, which required a number of simplifications to ensure both valid data and reasonable processing time. This resulted in very conservative criteria being applied to ensure valid data, but at the expense of both rigorous error analysis and the elimination of some otherwise valid data. With access to modern computing resources, the SuperDARN data processing methodology can be modernized to provide proper error estimates for the SuperDARN parameters (power, drift velocity, width). This research has resulted in 3 publications, which are presented here as Chapters 5, 6, and 7. The error analysis started with a first principles analysis of the self-clutter generated by the multiple-pulse technique that is used to probe the ionosphere (Chapter 5). Next, the statistical properties of voltage fluctuations as measured by SuperDARN were studied and the variance of these measurements were derived (Chapter 6). Finally, the statistical error analysis was propagated to the standard SuperDARN data products using a new First-Principles Fitting Methodology (Chapter 7). These results can be applied to all previously recorded SuperDARN data and have shown a practical increase in data of >50%. This has significant impact on the SuperDARN and space science communities with respect to, for example, global convection maps and their use in global modelling efforts. These results also enable quantitative experiment design facilitating research into using SuperDARN to provide electron density measurements, with a preliminary investigation using the new SuperDARN fitting methodology presented in Chapter 8

Middle Atmosphere Program. Handbook for MAP, volume 20

Various topics related to investigations of the middle atmosphere are discussed. Numerical weather prediction, performance characteristics of weather profiling radars, determination of gravity wave and turbulence parameters, case studies of gravity-wave propagation, turbulence and diffusion due to gravity waves, the climatology of gravity waves, mesosphere-stratosphere-troposphere radar, antenna arrays, and data management techniques are among the topics discussed

Thirteenth International Laser Radar Conference

One hundred fifteen papers were presented in both oral and poster sessions. The topics of the conference sessions were: spaceborne lidar applications; extinction/visibility; differential absorption lidar; winds and tropospheric studies; middle atmosphere; clouds and multiple scattering; pollution studies; and new systems

Middle Atmosphere Program. Handbook for MAP, volume 28

Extended abstracts from the fourth workshop on the technical and scientific aspects of MST (mesosphere stratosphere troposphere) radar are presented. Individual sessions addressed the following topics: meteorological applications of MST and ST radars, networks, and campaigns; dynamics of the equatorial middle atmosphere; interpretation of radar returns from clear air; techniques for studying gravity waves and turbulence; intercomparison and calibration of wind and wave measurements at various frequencies; progress in existing and planned MST and ST radars; hardware design for MST and ST radars and boundary layer/lower troposphere profilers; signal processing; and data management

Real-time processing of radar return on a parallel computer

NASA is working with the FAA to demonstrate the feasibility of pulse Doppler radar as a candidate airborne sensor to detect low altitude windshears. The need to provide the pilot with timely information about possible hazards has motivated a demand for real-time processing of a radar return. Investigated here is parallel processing as a means of accommodating the high data rates required. A PC based parallel computer, called the transputer, is used to investigate issues in real time concurrent processing of radar signals. A transputer network is made up of an array of single instruction stream processors that can be networked in a variety of ways. They are easily reconfigured and software development is largely independent of the particular network topology. The performance of the transputer is evaluated in light of the computational requirements. A number of algorithms have been implemented on the transputers in OCCAM, a language specially designed for parallel processing. These include signal processing algorithms such as the Fast Fourier Transform (FFT), pulse-pair, and autoregressive modelling, as well as routing software to support concurrency. The most computationally intensive task is estimating the spectrum. Two approaches have been taken on this problem, the first and most conventional of which is to use the FFT. By using table look-ups for the basis function and other optimizing techniques, an algorithm has been developed that is sufficient for real time. The other approach is to model the signal as an autoregressive process and estimate the spectrum based on the model coefficients. This technique is attractive because it does not suffer from the spectral leakage problem inherent in the FFT. Benchmark tests indicate that autoregressive modeling is feasible in real time

Applications in Low-Power Phased Array Weather Radars

Low-cost X-band radars are an emerging technology that offer significant advantages over traditional systems for weather remote sensing applications. X-band radars provide enhanced angular resolution at a fraction of the aperture size compared to larger, lower frequency systems. Because of their low cost and small form factor, these radars can now be integrated into more research and commercial applications. This work presents research and development activities using a low-cost, X-band (9410 MHz) Phase-Tilt Radar. The phase-tilt design is a novel phased array architecture that allows for rapid electronic scanning in azimuth and mechanical tilting in elevation, as a compromise between cost and performance. This work focuses on field studies and experiments in three meteorological applications. The first stage of research focuses on the real-world application of phased array radars in forest fire monitoring and observation. From April to May 2013, a phase-tilt radar was deployed to South Australia and underwent a field campaign to make polarimetric observations of prescribed burns within and around the Adelaide Hills region. Measurements show the real-time evolution of the smoke plume dynamics at a spatial and temporal resolution that has never before been observed with an X-band radar. This dissertation will perform data analysis on results from this field campaign. Results are compared against existing work, theories, and approaches. In the second stage of research, field experiments are performed to assess the data quality of X-band phased array radars. Specifically, this research focuses on the measurement of and techniques to improve the variance of weather product estimators for dual-polarized systems. Variability in the radar products is a complicated relationship between the radar system specifications, scanning strategy, and the physics governing precipitation. Here, the variance of the radar product estimators is measured using standard radar scanning strategies employed in traditional mechanical antenna systems. Results are compared against adaptive scan strategies such as beam multiplexing and frequency diversity. This work investigates the improvement that complex scanning strategies offer in dual-polarized, X-band phased array radar systems. In the third stage of research, simulations and field experiments are conducted to investigate the performance benefits of adaptive scanning to optimize the data quality of radar returns. This research focuses on the development and implementation of a waveform agile and adaptive scanning strategy to improve the quality of weather product estimators. Active phased array radars allow radar systems to quickly vary both scan pointing angles and waveform parameters in response to real-time observations of the atmosphere. As an evolution of the previous research effort, this work develops techniques to adaptively change the scan pointing angles, transmit and matched filter waveform parameters to achieve a desired level of data quality. Strategies and techniques are developed to minimize the error between observed and desired data quality measures. Simulation and field experiments are performed to assess the quality of the developed strategies