Ramp-sequence based frequency modulated continuous wave (FMCW) radar is effective in detecting the range and velocity of a target. However, because the target detection algorithm is based on a two-step fast Fourier transform (FFT) over several pulse-repetition intervals (PRIs), a significant amount of data must be processed in order to detect the range and velocity of target. In specific cases, when multiple channels must be supported in order to estimate the angle position of a target, even more hardware resources and memory, as well as longer processing times, are required. In this paper, a field programmable gate array (FPGA) based radar detection algorithm with a parallel and pipelined architecture is implemented in order to support the multi-channel processing of the algorithm, which includes range and Doppler processing, digital beam forming (DBF), and constant false alarm rate (CFAR) detection. In order to effectively support the parallel and pipelined architecture, we propose a data-routing-schemed DBF and fine-grained DBF architecture. The results from implementation of the proposed hardware resources and processing times are also presented. The implemented radar sensor is installed on an experimental vehicle and is demonstrated in the field.
The relation between beamforming and related beamspace high resolution direction-of-arrival (DOA) estimation is studied in this paper. Good DOA estimates are obtainable by applying MUSIC to the beam outputs directly. DOA estimation performance is related to the beamforming angle and inter-beam angle. This paper uses the forward-backward spatial smoothing technique as the preprocessor of beamspace MUSIC. We show by computer simulation that DOA estimates vary with inter-beam angle. We also show that DOA estimates of beamspace MUSIC are changed with beamforming angle.
We implemented a real-time radar system for an unmanned ground vehicle designed to run on unpaved or bumpy roads. The system must be able to detect slow targets in a cluttered environment and cover wide angular sections with high resolution at the same time. The system consists of array antennas, preprocessors for digital beam forming, and digital signal processors for the detection process which uses sawtooth waveforms and high-resolution estimation, and is called forward/backward spatial smoothing beamspace multiple signal classification (FBSS BS-MUSIC). We show that the sawtooth waveforms enhance the angular estimation capability of FBSS BS-MUSIC in addition to their well-known advantages of removing the ambiguity of targets and detecting slow targets with improved velocity resolution. This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/ by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. ⓒ
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.