The Fundamentals of Radar with Applications to Autonomous Vehicles

Radar systems can be extremely useful for applications in autonomous vehicles. This paper seeks to show how radar systems function and how they can apply to improve autonomous vehicles. First, the basics of radar systems are presented to introduce the basic terminology involved with radar. Then, the topic of phased arrays is presented because of their application to autonomous vehicles. The topic of digital signal processing is also discussed because of its importance for all modern radar systems. Finally, examples of radar systems based on the presented knowledge are discussed to illustrate the effectiveness of radar systems in autonomous vehicles

MilliSonic: Pushing the Limits of Acoustic Motion Tracking

Recent years have seen interest in device tracking and localization using acoustic signals. State-of-the-art acoustic motion tracking systems however do not achieve millimeter accuracy and require large separation between microphones and speakers, and as a result, do not meet the requirements for many VR/AR applications. Further, tracking multiple concurrent acoustic transmissions from VR devices today requires sacrificing accuracy or frame rate. We present MilliSonic, a novel system that pushes the limits of acoustic based motion tracking. Our core contribution is a novel localization algorithm that can provably achieve sub-millimeter 1D tracking accuracy in the presence of multipath, while using only a single beacon with a small 4-microphone array.Further, MilliSonic enables concurrent tracking of up to four smartphones without reducing frame rate or accuracy. Our evaluation shows that MilliSonic achieves 0.7mm median 1D accuracy and a 2.6mm median 3D accuracy for smartphones, which is 5x more accurate than state-of-the-art systems. MilliSonic enables two previously infeasible interaction applications: a) 3D tracking of VR headsets using the smartphone as a beacon and b) fine-grained 3D tracking for the Google Cardboard VR system using a small microphone array

High-resolution three-dimensional imaging radar

A three-dimensional imaging radar operating at high frequency e.g., 670 GHz, is disclosed. The active target illumination inherent in radar solves the problem of low signal power and narrow-band detection by using submillimeter heterodyne mixer receivers. A submillimeter imaging radar may use low phase-noise synthesizers and a fast chirper to generate a frequency-modulated continuous-wave (FMCW) waveform. Three-dimensional images are generated through range information derived for each pixel scanned over a target. A peak finding algorithm may be used in processing for each pixel to differentiate material layers of the target. Improved focusing is achieved through a compensation signal sampled from a point source calibration target and applied to received signals from active targets prior to FFT-based range compression to extract and display high-resolution target images. Such an imaging radar has particular application in detecting concealed weapons or contraband

One-Bit Algorithm Considerations for Sparse PMCW Radar

Phase Modulated Continuous Wave (PMCW) radar an emerging technology for autonomous cars. It is more flexible than the current frequency modulated systems, offering better detection resolution, interference mitigation, and future development opportunities. The issue preventing PMCW adoption is the need for high sample-rate analog to digital converters (ADCs). Due to device limits, a large increase in cost and power consumption occurs for every added resolution bit for a given sampling rate. This thesis explores radar detection techniques for few-bit and 1-bit ADC measurements. 1-bit quantization typically results in poor amplitude estimation, which can limit detections if the target signals are weak. Time Varying quantization Thresholds (TVTs) are a way to preserve that amplitude information. An existing few-bit Fast Iterative Shrinkage Thresholding Algorithm (FISTA) was adapted to use 1-bit TVT quantization. Three test scenarios compared the original FISTA using 1 and 2-bit quantization to the TVT approach. Tests included widely spaced targets, adjacent targets, and high dynamic range targets. Performance metrics included normalized mean squared error (NMSE) of target amplitude estimation and Receiver operating characteristic (ROC) curves for detection accuracy. Results showed the TVT implementation operated over the widest range of SNR values, had the lowest amplitude estimate NMSE at high SNR, and comparable NMSE with 2-bit FISTA at low SNR. There was an $84-93\%$ reduction in NMSE compared to 1-bit FISTA without TVTs. Few-bit FISTA had the best detection rates at specific SNR values, but was more sensitive to noise. AUC values averaged across the full SNR range for TVT FISTA were the most robust, measuring $13-46\%$ higher than 1-bit FISTA and $48-74\%$ higher than 2-bit FISTA. Advisor: Andrew Harm

Collimated beam FMCW radar for vital sign patient monitoring

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Patient monitoring of vital signals such as breathing rhythm and heart beat rate can be done remotely by the use of a radar system. This approach is advantageous since it does not require any contact with the patient. Obviously contactless monitoring results in a more comfortable situation for the patient, and in occasions it is almost mandatory as in the case of heavy burnt or newborn patients. Moreover, additional information such movement patterns are also available. A 120 GHz FMCW radar is described with special focus on the design, construction and testing of a specific reflector antenna for the system. The system is based on a commercial radar chipset that includes its own antennas. The challenge has been to design the optimum reflector and to build it and test it in a cost effective way. The reflector has been 3D printed and a near-field testing technique has been implemented to assess its performance. The results show that the system is able to measure the vital signs at distances beyond one meter.Postprint (author's final draft

A New Multistatic FMCW Radar Architecture by Over-the-Air Deramping

© 2015 IEEE. Frequency modulated continuous wave (FMCW) radar is widely adopted solution for low-cost, short to medium range sensing applications. However, a multistatic FMCW architecture suitable for meeting the low-cost requirement has yet to be developed. This paper introduces a new FMCW radar architecture that implements a novel technique of synchronizing nodes in a multistatic system, known as over-the-air deramping (OTAD). The architecture uses a dual-frequency design to simultaneously broadcast an FMCW waveform on a lower frequency channel directly to a receiver as a reference synchronization signal, and a higher frequency channel to illuminate the measurement scene. The target echo is deramped in hardware with the synchronization signal. OTAD allows for low-cost multistatic systems with fine range-resolution, and low peak power and sampling rate requirements. Furthermore, the approach avoids problems with direct signal interference. OTAD is shown to be a compelling solution for low-cost multistatic radar systems through the experimental measurements using a newly developed OTAD radar system

Remote Human Vital Sign Monitoring Using Multiple-Input Multiple-Output Radar at Millimeter-Wave Frequencies

Non-contact respiration rate (RR) and heart rate (HR) monitoring using millimeter-wave (mmWave) radars has gained lots of attention for medical, civilian, and military applications. These mmWave radars are small, light, and portable which can be deployed to various places. To increase the accuracy of RR and HR detection, distributed multi-input multi-output (MIMO) radar can be used to acquire non-redundant information of vital sign signals from different perspectives because each MIMO channel has different fields of view with respect to the subject under test (SUT). This dissertation investigates the use of a Frequency Modulated Continuous Wave (FMCW) radar operating at 77-81 GHz for this application. Vital sign signal is first reconstructed with Arctangent Demodulation (AD) method using phase change’s information collected by the radar due to chest wall displacement from respiration and heartbeat activities. Since the heartbeat signals can be corrupted and concealed by the third/fourth harmonics of the respiratory signals as well as random body motion (RBM) from the SUT, we have developed an automatic Heartbeat Template (HBT) extraction method based on Constellation Diagrams of the received signals. The extraction method will automatically spot and extract signals’ portions that carry good amount of heartbeat signals which are not corrupted by the RBM. The extracted HBT is then used as an adapted wavelet for Continuous Wavelet Transform (CWT) to reduce interferences from respiratory harmonics and RBM, as well as magnify the heartbeat signals. As the nature of RBM is unpredictable, the extracted HBT may not completely cancel the interferences from RBM. Therefore, to provide better HR detection’s accuracy, we have also developed a spectral-based HR selection method to gather frequency spectra of heartbeat signals from different MIMO channels. Based on this gathered spectral information, we can determine an accurate HR even if the heartbeat signals are significantly concealed by the RBM. To further improve the detection’s accuracy of RR and HR, two deep learning (DL) frameworks are also investigated. First, a Convolutional Neural Network (CNN) has been proposed to optimally select clean MIMO channels and eliminate MIMO channels with low SNR of heartbeat signals. After that, a Multi-layer Perceptron (MLP) neural network (NN) is utilized to reconstruct the heartbeat signals that will be used to assess and select the final HR with high confidence

Coffee Can Radar: Detection and Jamming

This project models the operation of an interception-resistant automotive radar and demonstrates its susceptibility to jamming. The initial hardware design was based on open courseware from MIT Lincoln Laboratory. Prior to the construction of the radar, expected results were recorded using MATLAB and LTspice simulations. The interference signals were designed in MATLAB and transmitted using a software-defined radio. Final testing was completed using a spectrum analyzer and software designed to plot the time-lapsed location of a detected object