Faruk Uysal

Signal decomposition for wind turbine clutter mitigation

This paper addresses the problem of dynamic clutter mitigation by focusing on the mitigation of the wind turbine clutter from the radar data. The basis pursuit and morphological component analysis approach are used to decompose the radar returns into the sum of oscillatory and transient components. The success of the morphological component analysis rely on sparsity, thus different transform domains needs to be identified correctly to represent each component sparsely. The method is illustrated on a radar data collected from a small custom built radar system to show the success of the proposed algorithm for wind turbine clutter mitigation.

Mitigation of Wind Turbine Clutter for Weather Radar by Signal Separation

This paper addresses the mitigation of wind turbine clutter (WTC) in weather radar data in order to increase the performance of existing weather radar systems and to improve weather analyses and forecasts. We propose a novel approach for this problem based on signal separation algorithms. We model the weather signal as group sparse in the time-frequency domain; in parallel, we model the WTC signal as having a sparse time derivative. In order to separate WTC and the desired weather returns, we formulate the signal separation problem as an optimization problem. The objective function to be minimized combines total variation regularization and time-frequency group sparsity. We also propose a three-window short-time Fourier transform for the time-frequency representation of the weather signal. To show the effectiveness of the proposed algorithm on weather radar systems, the method is applied to simulated and real data from the next-generation weather radar network. Significant improvements are observed in reflectivity, spectral width, and angular velocity estimates.

Waveform design for wideband beampattern and beamforming

This paper considers wideband beamforming and waveform design for transmission from advanced multiple channel radar systems. Hence, this paper describes the initial designs of a wideband transmit beamformer for a multi-channel high resolution radar, applicable to airborne and spaceborne radars. As a case study for this paper, we use the EcoSAR instrument developed by NASA Goddard Space Flight Center for the measurement of science parameters. The wideband EcoSAR employs two multi-channel antennas and full transmit and receive digital beamforming to generate high resolution images of the ground features. Maintaining a consistent beampattern when the bandwidth is approximately 50% of the center frequency is a challenge. Breaking this nexus relies on optimum beam weight design and accompanying waveform design; not merely the former as is typically done. The approaches of this paper have shown how the beampatterns can be maintained while meeting beam requirements.

Dynamic Clutter Mitigation Using Sparse Optimization

The impact of wind farms on radar systems, such as air traf-fc control (ATC), air defense (AD), and weather radars, is a signifcant issue, especially considering that demand for wind power and wind farms is increasing dramatically. According to the American Wind Energy Association, more than 51,630 MW of wind power capacity are installed in the United States [1]. There are also more than 8,900 MW of wind power capacity under construction, involving more than 90 separate projects spanning 31 states and Puerto Rico [2].

Joint Along Track Interferometry and Space-Time Adaptive Processing for target detection and geolocation

This paper presents a new adaptive radar signal processing technique for target detection and geolocation using radar data from platforms capable of performing simultaneous Synthetic Aperture Radar (SAR) and Along-Track Interferometry (ATI). Space-Time Adaptive Processing (STAP) and ATI processing methodologies are combined in parallel to simultaneously image, detect and identify the geolocation of moving targets over clutter using data obtained from a single set of measurements. Proposed method allows use of a common data source and interconnected methods to fully exploit the information content of the measured data for improved target detection and geolocation.

Target geolocation in Gotcha data using cross-channel interferometry

This paper discusses application of a cross-channel interferogram based technique for target geolocation to data from the Gotcha sensor. A modified SAR/ATI/STAP geolocation method is used to compensate for the inability to perform STAP well using the available Gotcha data due to limitations in spatial degrees of freedom. SAR/ATI geolocation is illustrated with three examples from the measurements for: two known targets with truth data, and an unknown target. The first known target is geolocated with a 15.6m accuracy; the unknown target is geolocated with reasonable accuracy for 8 out of 11 detections; and the second known target is geolocated with an average error of 13.18m for 10 consecutive CPIs.

Application of waveform weighting for a frequency- invariant transmit beampattern

Advanced radar systems rely on multichannel, wideband operation. NASAs Ecosystem SAR (EcoSAR) and second-generation digital beamforming SAR [1]–[3] use active array architectures, where an active array radar system contains independent transmit and receive chains with unique amplifiers for each antenna element in the multichannel system. These radar systems have an independent arbitrary waveform generator for each channel and are designed to address wideband transmit beamforming. Unlike conventional narrowband beamforming, which only require a unique set of beamsteering coefficients per look angle, wideband beamforming requires beamsteering coefficients that vary with both look angle and frequency.

Digital radar implementation with amplitude predistortion

The modern advancements in digital electronics allow waveforms to be easily synthesized and captured using only digital electronics. The synthesis of radar waveforms using only digital electronics, such as Digital-to-Analog Converters (DACs) and Analog-to-Digital Converters (ADCs) allows for a majority of the analog chain to be removed from the system. In order to create a constant amplitude waveform, the amplitude distortions must be compensated for. The method chosen to compensate for the amplitude distortions is to pre-distort the waveform so, when it is influenced by the system, the output waveform has a near constant amplitude modulus. The effects of the predistortion were observed to be successful in both range and range-Doppler radar implementations.

Comparison of range migration correction algorithms for range-Doppler processing

Abstract. The next generation digital radars are able to provide high-range resolution by the advancement of radar hardware technologies. These systems take advantage of coherent integration and Doppler processing technique to increase the target’s signal-to-noise ratio. Due to the high-range resolution (small range cells) and fast target motion, a target migrates through multiple range cells within a coherent processing interval. Range cell migration (also known as range walk) occurs and degrades the coherent integration gain. There are many approaches in the literature to correct these unavoidable effects and focus the target in the range-Doppler domain. We demonstrate some of these methods on an operational frequency-modulated continuous-wave (FMCW) radar and point out practical issues in the application.

The effect of moving target on range-doppler map and backprojection algorithm for focusing

Range migration is unavoidable and cannot be neglected in pulse Doppler radar when target velocity is high and/or wideband transmit signals are used. In this paper, we investigate the range and Doppler degradation due to target motion in wideband pulse Doppler radar. To correct range cell migration, an alternative focusing method is introduced by using the backprojection algorithm. The success of the method is shown by simulations.