Radar Landmark Suitability Assessment for Vehicle Localization
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Solution Overview
Problem
Current landmark-based self-localization methods for vehicles are not robust enough due to the complexity of the automotive environment, as they rely on single-scan observations and are not designed for the automotive environment, leading to inaccuracies in determining suitable positional references for precise geographical mapping.
Innovation Solution
A vehicle-based method that analyzes radar returns using a receive antenna array to determine the suitability of objects as landmarks by assessing criteria such as stationarity, single scatterer status, and variation of radar parameters with azimuthal angle, incorporating Doppler analysis and radar cross-section measurements to classify potential landmarks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If single-scan observation methods are used for landmark detection, then the processing speed is fast, but the reliability of landmark identification is insufficient due to environmental complexity
Solution Approach 1:
The patent applies preliminary action by performing multiple radar scans before final landmark identification. The system accumulates detection data from multiple scans, pre-processes the information to identify potential landmarks, and then validates them against multiple criteria (stationarity, single scatterer status, azimuthal angle consistency) before final selection. This preliminary multi-scan observation resolves the contradiction by ensuring reliable identification through repeated measurements while maintaining structured processing complexity.
Solution Approach 2:
The patent implements feedback mechanisms where detection results from each scan are fed back into the processing system. The system continuously updates its understanding of the environment by comparing new scans with previous ones, refining landmark candidates through iterative validation. This feedback loop allows the system to improve reliability over time while managing complexity through systematic data reuse and comparison.
2Measurement precision
If multiple criteria analysis is performed for landmark classification, then the measurement precision of landmark suitability is improved, but the processing time and computational complexity increase
Solution Approach 1:
The patent segments the landmark assessment process into distinct, independent criteria evaluations: stationarity determination, single scatterer status verification, and azimuthal angle variation analysis. Each criterion is evaluated separately using dedicated processing routines, allowing the system to achieve high measurement precision through comprehensive multi-criteria analysis while managing computational complexity through modular, segmented processing of each assessment dimension.
3Measurement precision
If radar parameters are analyzed across multiple azimuthal angles, then the accuracy of landmark classification is improved, but the quantity of data to be processed increases
Solution Approach 1:
The patent extracts only the essential and relevant features from the comprehensive radar data set. Instead of processing all raw radar returns, the system selectively extracts key parameters: stationarity indicators, single scatterer characteristics, and azimuthal angle variations. This extraction approach maintains high classification accuracy by focusing on discriminative features while significantly reducing the quantity of data that requires intensive processing.
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
This method improves the precision of radar-based SLAM by identifying reliable and robust landmarks, enhancing the accuracy of geographical positioning techniques, such as GPS superposition, by classifying objects as high-quality landmarks based on their stability and consistent reflectivity patterns across different angles.
Implementation Method 1
a vehicle-based radar system adapted to transmit radar signals and receive reflected radar detections from objects in the vicinity of the vehicle
Implementation Method 2
Step d) may comprise analyzing range profiles and Doppler profiles of the radar returns across the plurality of antennas
Data Source
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AI summary
A vehicle-based method to determine the suitability of an object in the vicinity of a vehicle as a suitable positional landmark, comprising the steps of: a) emitting a plurality of radar signals from a vehicle; b) detecting the radar returns from said emitted radar signals reflected by said object; c) analyzing at least one parameter of at least one radar return to determine the extent to which said object is a stationary object; d) analyzing at least one parameter of at least one radar return to determine the extent to which said object is a single scatterer; e) analyzing at least one parameter of a plurality of radar returns to determine the extent to which said parameter varies with the azimuthal angle between said vehicle and said object, f) determining the suitability of said landmark for the results of steps c), d) and e).