The aim of this pro ject was to evaluate the use of SIMD array architectures in radar signal processing. This has been done by implementing one of the most demanding parts of the radar signal processing chain for airborne radar on the CSX600 architecture devel- oped by Clearspeed Technologies. The CSX600 architecture is a SIMD processor with 96 processing elements which can be arranged either as a linera array or as a ring. The QR- decomposition, which was the part chosen for implementation, is the most performance demanding part of the STAP stage. In order to create a relevant test case the well known RT STAP benchmark from Mitre Corporation has been used. Two different algorithms for performing QR-decompositions have been implemented and verified. In both cases it has been concluded that either longer (> ≈256) or shorter (< ≈32) processor array lengths would, in general, yield a higher utilization ratio. The FLOP count and utiliza- tion has been measured for both algorithms, and it has been concluded that at least eight CSX600 processors are needed to meet the real-time demand of the benchmark.

Thesis (M.S.) in Electrical Engineering--University of Maine, 2009. / Includes vita. Includes bibliographical references (leaves 63-65).

Thesis (M.S.)--Brigham Young University. Dept. of Electrical and Computer Engineering, 1998. / Includes bibliographical references (p. 89-90).

Radar offers unique advantages over other sensors for the detection of humans, such as remote operation during virtually all weather and lighting conditions, increased range, and better coverage. Many current radar-based human detection systems employ some type of Fourier analysis, such as Doppler processing. However, in many environments, the signal-to-noise ratio (SNR) of human returns is quite low. Furthermore, Fourier-based techniques assume a linear variation in target phase over the aperture, whereas human targets have a highly nonlinear phase history. The resulting phase mismatch causes significant SNR loss in the detector itself. In this work, human target modeling is used to derive a more accurate non-linear approximation to the true target phase history. Two algorithms are proposed: a parameter estimation-based optimized non-linear phase (ONLP) detector, and a dictionary search-based enhanced optimized non-linear phase (EnONLP) detector. The ONLP algorithm optimizes the likelihood ratio over the unknown model parameters to derive a more accurate approximation to the expected human return. The EnONLP algorithm stores expected target signatures generated for each possible combination of model parameters in a dictionary, and then applies Orthogonal Matching Pursuit (OMP) to determine the optimal linear combination of dictionary entries that comprises the measured radar data. Thus, unlike the ONLP, the EnONLP algorithm also has the capability of detecting the presence of multiple human targets. Cramer-Rao bounds (CRB) on parameter estimates and receiver operating characteristics (ROC) curves are used to validate analytically the performance of both proposed methods to that of conventional, fully adaptive STAP. Finally, application of EnONLP to target characterization is illustrated.

This dissertation analyzes the capability of multiple-input, multiple-output (MIMO) radar techniques to improve the image quality and area-coverage rate of synthetic aperture imaging systems. A signal processing architecture for MIMO radar is used to understand the applicability of MIMO for synthetic aperture radar (SAR) and synthetic aperture sonar (SAS) systems. MIMO SAR/SAS is shown to be a natural extension of standard multichannel synthetic aperture imaging techniques to exploit transmit degrees of freedom in addition to those used on receive. Degradation in range sidelobe performance and the associated impact on image quality is identified as a key impediment to MIMO SAR/SAS. A novel mismatched filtering approach is presented to mitigate this issue. New results in sampling theory are derived that allow the aliasing that occurs when a wide-sense stationary random process is non-uniformly sampled to be quantified. These results are applied to the case of recurrent sampling and used to quantify the impact of azimuth ambiguities on MIMO SAR/SAS image contrast.

No description available.

The detection of weak, ground-moving targets can be improved through effective utilization of additional target signal energy collected over an extended dwell time. The signal model used in conventional radar processing limits integration of signal energy over an extended dwell. Two solutions that consider the complexity of the extended-dwell signal model and effectively combine signal energy collected over a long dwell are presented. The first solution is a single-channel algorithm that provides an estimate of the optimal detector to maximize output signal-to-interference-plus-noise ratio for the extended dwell time signal. Rather than searching for the optimal detector in an intractably large filter bank that contains all combinations of phase components, the single-channel algorithm projects dictionary entries against the data to estimate the signal’s linear and nonlinear phase components sequentially with small, phase-specific dictionaries in a multistage process. When used as the detector, the signal model formed from the estimated phase components yields near optimal performance for a wide range of target parameters for dwell times up to four seconds. In comparison, conventional radar processing methods are limited to an integration time of approximately 100 milliseconds. The second solution is a multichannel, multistage algorithm based on element-space pre-Doppler space-time-adaptive processing with two modifications that make it suitable for detection of weak targets whose energy is collected over an extended dwell time. The multichannel solution detects targets with lower radial velocities at significantly lower signal-to-noise ratios (SNRs) than conventional radar processing methods. The decrease in required input SNR for the multichannel solution as compared to conventional methods nearly doubles the detection range for a typical target of interest. Future related research includes extension of these concepts to other radar applications and investigation of algorithm performance for the multiple-target scenario.

This thesis presents work done to extend and improve the operation of homodyne dechirp-on-receive linearly frequency modulated radars. First, an investigation of the effect of common phase errors on the point response function of the radar is described. The dependence on the window function of the degradation due to phase errors is investigated, and a simple, precise, and general approach for calculating the degraded Point Spread Function (PSF) is described and demonstrated. This method is shown to be particularly useful when investigating the effect of chirp nonlinearity on the PSF. Next, a method for focussing range profiles that are degraded by chirp nonlinearity is described. This method is based on two established methods, the Phase Gradient Algorithm (PGA) and a time-domain re-sampling technique. The technique is entirely hardware independent, allowing any homodyne dechirp-on-receive linearly frequency modulated radar to be focussed. Where suitable archive signal data exists, focussed imagery can even be produced from radars that no longer exist. The complete algorithm and details of the implementation are described, and the technique is demonstrated on three representative radar cases: extreme chirp nonlinearity, typical chirp nonlinearity, and a retrospective case. In all of the cases, it was shown that the PSF was dramatically improved. A technique based on down conversion by aliasing for reducing the required sampling rate is described, and a simple technique for calculating suitable sampling rates is presented. This method is demonstrated for a typical application in which sampling rate reduction might be required, namely Moving Target Indication (MTI). The MTI application is described and quantified, including a simple technique for choosing suitable radar operation parameters. The MTI technique with subsampling was demonstrated in software simulations and in a simple radar experiment. A Synthetic Aperture Radar (SAR) test bench for researching component performance and scatterer properties in the context of SAR was developed. An appropriate image formation processing algorithm was found and modified to better suit the task of a short data collection baseline and drifting centre frequencies, both of which are present in the test bench situation. Software was written to collect data, to control the hardware, and to process the signals into SAR images. A data simulator was written to test the image formation algorithm implementation; it also served as a useful tool for investigating the effect of signal errors on the quality of the resultant SAR imagery. A suitable oscillator was chosen for the task, based on phase noise and centre frequency stability considerations, both of which are quantified and discussed. Preliminary SAR imagery was produced, indicating that the system operates correctly and in agreement with comparable systems.

abstract: In the past half century, low-power wireless signals from portable radar sensors, initially continuous-wave (CW) radars and more recently ultra-wideband (UWB) radar systems, have been successfully used to detect physiological movements of stationary human beings. The thesis starts with a careful review of existing signal processing techniques and state of the art methods possible for vital signs monitoring using UWB impulse systems. Then an in-depth analysis of various approaches is presented. Robust heart-rate monitoring methods are proposed based on a novel result: spectrally the fundamental heartbeat frequency is respiration-interference-limited while its higher-order harmonics are noise-limited. The higher-order statistics related to heartbeat can be a robust indication when the fundamental heartbeat is masked by the strong lower-order harmonics of respiration or when phase calibration is not accurate if phase-based method is used. Analytical spectral analysis is performed to validate that the higher-order harmonics of heartbeat is almost respiration-interference free. Extensive experiments have been conducted to justify an adaptive heart-rate monitoring algorithm. The scenarios of interest are, 1) single subject, 2) multiple subjects at different ranges, 3) multiple subjects at same range, and 4) through wall monitoring. A remote sensing radar system implemented using the proposed adaptive heart-rate estimation algorithm is compared to the competing remote sensing technology, a remote imaging photoplethysmography system, showing promising results. State of the art methods for vital signs monitoring are fundamentally related to process the phase variation due to vital signs motions. Their performance are determined by a phase calibration procedure. Existing methods fail to consider the time-varying nature of phase noise. There is no prior knowledge about which of the corrupted complex signals, in-phase component (I) and quadrature component (Q), need to be corrected. A precise phase calibration routine is proposed based on the respiration pattern. The I/Q samples from every breath are more likely to experience similar motion noise and therefore they should be corrected independently. High slow-time sampling rate is used to ensure phase calibration accuracy. Occasionally, a 180-degree phase shift error occurs after the initial calibration step and should be corrected as well. All phase trajectories in the I/Q plot are only allowed in certain angular spaces. This precise phase calibration routine is validated through computer simulations incorporating a time-varying phase noise model, controlled mechanic system, and human subject experiment. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2018

Many radars suffer from masking of weaker targets by stronger ones due to range sidelobes of pulse compression codes. We propose a method to prevent this by successively detecting targets and canceling their effects. Performance of the proposed method will be investigated in various scenarios with regard to existence of noise, targets, and the Doppler effect.