Radar Sensor Data Processing for Angular Resolution and Side Lobe Suppression
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Solution Overview
Problem
Radar sensor systems with sparse transmit/receive unit distributions suffer from side lobes that interfere with accurate direction of arrival (DoA) determination of target objects, leading to reduced angular resolution and increased computational effort in data processing.
Innovation Solution
A method for radar sensor data processing that involves selecting angular spectrum components based on a defined signal value threshold, which decreases with increasing iteration steps, to exclude side lobes and include main lobes, thereby improving the accuracy of target object detection and reducing computational complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If transmit/receive units are arranged at larger and irregular distances to increase total antenna aperture, then angular resolution is improved, but side lobes are generated that interfere with accurate direction of arrival determination
Solution Approach 1:
The patent extracts and removes side lobes from the angular spectrum through iterative thresholding. By identifying and eliminating these unwanted components, the system achieves cleaner angular spectra that enable more accurate target detection despite the sparse sensor arrangement
Solution Approach 2:
The patent implements an iterative feedback process where the angular spectrum is processed repeatedly. In each iteration, side lobes are identified and removed based on threshold criteria, and the process continues until convergence. This feedback mechanism progressively improves the angular spectrum quality
2Measurement precision
If iterative algorithms like IMAT or CLEAN are used to eliminate side lobes, then direction of arrival determination is improved, but computational effort and processing time increase significantly
Solution Approach 1:
The patent applies a simplified thresholding approach that processes only the most significant angular spectrum components. By focusing computational resources on the dominant lobes rather than processing the entire spectrum exhaustively, the system achieves adequate side lobe suppression with reduced computational complexity
Solution Approach 2:
The patent dynamically adjusts the signal value threshold parameter across iterations. By adapting the threshold based on the current angular spectrum characteristics, the system optimizes the balance between side lobe removal effectiveness and computational efficiency
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
The method enhances the accuracy of target object detection by effectively eliminating side lobes and improving angular resolution, while also reducing computational effort and processing time in radar sensor data processing.
Implementation Method 1
Driving assistance systems in vehicles use radar sensors to detect a vehicle environment of the vehicle and to detect target objects in the vehicle environment
Implementation Method 2
the method described in 'A Unified Approach to Sparse Signal Processing,' F. Marvasti, A. Amini, F. Haddadi, M. Soltanolkotabi, B. H. Khalaj, A. Aldroubi, S. Sanei and J. Chambers, EURASIP Journal on Advances in Signal Processing, vol. 2012, No. 1, p. 44, February 2012, is, for example, used to convert the phase signals of the sensor array through a Fourier transform into an angular spectrum
Data Source
AI summary
A method for radar sensor data processing of radar sensor data of a radar sensor system detecting at least one target object in an environment of a carrier system. A radar sensor data processing system is also described.