Automotive Radar Range Segmentation for Lower Sampling Load
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Solution Overview
Problem
Radar sensors in automotive applications face challenges with high data volumes due to double sampling in multiple detection ranges, leading to increased computational and storage requirements.
Innovation Solution
The radar device employs separate or shared radar sensor components to detect distinct measuring ranges, using bandpass filters to suppress unnecessary frequency components and reduce data sampling rates, thereby optimizing data processing efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If separate or shared antennas are used to monitor far range and medium range with modified antenna hardware or digital beamforming, then detection capability in multiple ranges is improved, but data volume increases significantly
Solution Approach 1:
The patent divides the detection task into two separate measuring ranges (first measuring range for medium distance, second measuring range for far distance) with distinct distance intervals. By segmenting the monitoring areas and assigning different antenna configurations to each range, the system avoids redundant data generation while maintaining comprehensive detection coverage across both ranges
2Length of stationary object
If high sampling rates are used to achieve far range detection, then detection range is improved, but computational requirements and data processing load increase
Solution Approach 1:
The patent applies different sampling strategies to different measuring ranges based on their specific requirements. The first measuring range (medium distance) uses one sampling configuration while the second measuring range (far distance) uses a different sampling configuration optimized for its specific detection needs. This local optimization reduces overall computational requirements while maintaining adequate detection capability in both ranges
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 approach reduces data amounts and system costs while maintaining effective detection capabilities in both near and far ranges, enhancing computational efficiency and reducing power consumption.
Implementation Method 1
The radar sensors emit high-frequency radar beams via an antenna structure and receive the beams reflected at objects. The detected objects may be stationary or moving in this case. The distance and the direction, i.e., azimuth and/or elevation angles in relation to the object, may be calculated with the aid of the received radar beams.
Implementation Method 2
In FMCW (frequency modulated continuous wave) radar sensors, the emission frequency of a continuous radar signal is modulated in ramps. By mixing the received signal with the emitted signal, a baseband signal is generated which is subsequently evaluated.
Implementation Method 3
the transceiver unit includes a bandpass filter which is designed to suppress frequency components from a baseband signal generated by the transceiver unit for detecting the second measuring range which are less than a predefined minimum frequency.
Data Source
AI summary
A radar device including a transceiver unit and a signal processing unit. The transceiver unit detects a first measuring range including distances from the radar device in a first predefined distance range and outputs first sensor signals. The transceiver unit detects a second measuring range including distances from the radar device in a second predefined distance range and outputs second sensor signals. The signal processing unit evaluates the first and second sensor signals. The first distance range at least partially differs from the second distance range. The distances of the second distance range are greater than a predefined minimum distance.