Distributed Vehicle Radar Localization With Near-Field Beamforming
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Solution Overview
Problem
Traditional automotive radar devices face limitations in resolution due to small arrays, which prevent effective 3D localization of objects, and processing challenges arise from sparse antenna elements on curved surfaces like windshields, hindering the application of range-angle estimation methods.
Innovation Solution
A method involving a radar sensor device with distributed sending and receiving antennas, utilizing near-field beamforming and modified FFT algorithms to generate delay-doppler and range-angle maps, compensating for range migration and channel imbalances, and applying algorithms like CLEAN and matching pursuit for precise localization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If large arrays extending over the car width are used to achieve submersed degree resolution, then resolution capability is improved, but device complexity increases due to the need to address range migration and process large amounts of data
Solution Approach 1:
The patent divides the signal processing into distinct stages: first generating a delay-Doppler map from radar returns, then applying near-field beamforming to create a range-angle map. This segmentation allows complex processing to be broken down into manageable steps, each handling specific aspects of the data transformation and localization.
Solution Approach 2:
The patent introduces an intermediate delay-Doppler map as a representation of the radar scene before final localization. This intermediate structure serves as a mediator that bridges the raw radar data and the final range-angle localization, enabling systematic processing of range migration and spatial information.
2Adaptability or versatility
If sparse antenna elements are placed on curved surfaces like windshields, then adaptability to vehicle surfaces is improved, but measurement precision deteriorates due to difficulties in applying range-angle estimation methods
Solution Approach 1:
The patent transforms the processing parameters by first creating a delay-Doppler map that captures spatial information, then applying near-field beamforming with specific phase and amplitude weighting. This parameter transformation adapts the processing to accommodate sparse antenna elements on curved surfaces while maintaining localization accuracy through the modified beamforming approach.
3Measurement precision
If range resolution is made smaller than the approached length, then measurement precision is improved, but device complexity increases due to range migration effects that prevent straightforward application of estimation methods
Solution Approach 1:
The patent performs preliminary processing by first generating the delay-Doppler map to capture all spatial information before applying the near-field beamforming algorithm. This preliminary action separates the range migration effect from the final localization, allowing the beamforming to operate on pre-organized data that accounts for the curved array geometry and sparse element distribution.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables high-resolution 3D localization of objects with fine azimuth resolution and broad field of view, maximizing signal-to-noise ratio and allowing integration into curved vehicle surfaces, while reducing computational requirements.
Implementation Method 1
Radar radiation signals are emitted into the surroundings by a plurality of sending antennas of the radar sensor device... Radar radiation signals are captured, which were reflected by the at least one object, by a plurality of receiving antennas of the radar sensor device
Implementation Method 2
A nearfield-beaming algorithm is applied on the generated delay-doppler map by the electronic computing device. A range-angle map is generated depending on the applied nearfield-beamforming algorithm by the electronic computing device and the at least one object is localized in the range-angle map
Implementation Method 3
for generating the delay-doppler map the radar radiation signals are analyzed by a fast-Fourier-transformation algorithm
Data Source
Figure 1~2
AI summary
A method for localizing at least one object (7) in surroundings (8) of a motor vehicle (1) by a radar sensor device (2) of the motor vehicle (1), comprising the steps of: emitting radar radiation signals (9) into the surroundings (8) by a plurality of sending antennas (3) of the radar sensor device (2), wherein the plurality of sending antennas (3) is distributed attached at the motor vehicle (1); capturing radar radiation signals (10), which were reflected by the at least one object (7), by a plurality of receiving antennas (4) of the radar sensor device (2)(, wherein the plurality of receiving antennas (4) is distributed attached at the motor vehicle (1); generating a delay-doppler map (13) for the surroundings (8) depending on the emitted radar radiations signals (9) and the received radar radiation signals (10) by an electronic computing device (5) of the radar sensor device (2); applying a nearfield-beaming algorithm on the generated delay-doppler map (13) by the electronic computing device (5); generating a range-angle map (15) depending on the applied nearfield-beamforming algorithm by the electronic computing device (5); and localizing the at least one object (7) in the range-angle map (15) by the electronic computing device (5). Furthermore, the present invention relates to a computer program product, a computer-readable storage medium, as well as to a radar sensor device (2).