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

Frequency-modulated continuous-wave LiDAR compressive depth-mapping

We present an inexpensive architecture for converting a frequency-modulated continuous-wave LiDAR system into a compressive-sensing based depth-mapping camera. Instead of raster scanning to obtain depth-maps, compressive sensing is used to significantly reduce the number of measurements. Ideally, our approach requires two difference detectors. % but can operate with only one at the cost of doubling the number of measurments. Due to the large flux entering the detectors, the signal amplification from heterodyne detection, and the effects of background subtraction from compressive sensing, the system can obtain higher signal-to-noise ratios over detector-array based schemes while scanning a scene faster than is possible through raster-scanning. %Moreover, we show how a single total-variation minimization and two fast least-squares minimizations, instead of a single complex nonlinear minimization, can efficiently recover high-resolution depth-maps with minimal computational overhead. Moreover, by efficiently storing only $2m$ data points from $m<n$ measurements of an $n$ pixel scene, we can easily extract depths by solving only two linear equations with efficient convex-optimization methods

External modulation method for generating accurate linear optical FMCW

Frequency modulation continuous wave (FMCW) lasers are key components in modern optical imaging. However, current intracavity modulation lasers do not exhibit low-frequency jitter rate and high linearity due to the inherent relaxation oscillations. Although this may be compensated in a direct modulation laser diode using an optoelectronic feedback loop, the available sweep speed is moderately small. In this letter, a special external modulation method is developed to improve the performance of FMCW. Since only the first sideband optical field is used during the entire generation process, phase noise is kept to a minimum and is also independent of the sweep speed. We demonstrate that the linearity and jitter rates do not deteriorate appreciably when the sweep speed is changed over three orders of magnitude, even up to the highest sweep speed of 2.5 GHz/ μs

RadarSLAM: Radar based Large-Scale SLAM in All Weathers

Numerous Simultaneous Localization and Mapping (SLAM) algorithms have been presented in last decade using different sensor modalities. However, robust SLAM in extreme weather conditions is still an open research problem. In this paper, RadarSLAM, a full radar based graph SLAM system, is proposed for reliable localization and mapping in large-scale environments. It is composed of pose tracking, local mapping, loop closure detection and pose graph optimization, enhanced by novel feature matching and probabilistic point cloud generation on radar images. Extensive experiments are conducted on a public radar dataset and several self-collected radar sequences, demonstrating the state-of-the-art reliability and localization accuracy in various adverse weather conditions, such as dark night, dense fog and heavy snowfall

Penetrating 3-D Imaging at 4- and 25-m Range Using a Submillimeter-Wave Radar

We show experimentally that a high-resolution imaging radar operating at 576–605 GHz is capable of detecting weapons concealed by clothing at standoff ranges of 4–25 m. We also demonstrate the critical advantage of 3-D image reconstruction for visualizing hidden objects using active-illumination coherent terahertz imaging. The present system can image a torso with <1 cm resolution at 4 m standoff in about five minutes. Greater standoff distances and much higher frame rates should be achievable by capitalizing on the bandwidth, output power, and compactness of solid state Schottky-diode based terahertz mixers and multiplied sources

FMCW rail-mounted SAR: Porting spotlight SAR imaging from MATLAB to FPGA

In this work, a low-cost laptop-based radar platform derived from the MIT open courseware has been implemented. It can perform ranging, Doppler measurement and SAR imaging using MATLAB as the processor. In this work, porting the signal processing algorithms onto a FPGA platform will be addressed as well as differences between results obtained using MATLAB and those obtained using the FPGA platform. The target FPGA platforms were a Virtex6 DSP kit and Spartan3A starter kit, the latter was also low-cost to further reduce the cost for students to access radar technology