Radar Signal Compression Using Adaptive Doppler and Range Factors
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Solution Overview
Problem
Radar systems, particularly automotive radar systems, face challenges with high memory and processing requirements due to the large number of data points generated from high-resolution measurements, which can be exacerbated by differences in received power and noise levels, leading to increased complexity in data compression and signal processing.
Innovation Solution
A data compression method is implemented using a radar transceiver that determines a compression factor based on the probability of object collision, path loss, and Doppler Effect characteristics, employing techniques such as Fast Fourier Transform (FFT) and lossy compression to reduce data storage needs, while storing compressed data in a multidimensional array with adaptive memory allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high resolution radar measurements are used to increase measurement precision, then distance and velocity detection accuracy is improved, but memory requirements and processing power increase significantly
Solution Approach 1:
The patent extracts and processes radar data in sequential stages, separating distance information (range bins) from velocity information (Doppler bins) in distinct processing steps. This allows the system to handle large datasets by processing them in manageable portions rather than loading all data simultaneously into memory, thereby reducing peak memory requirements while maintaining high measurement precision.
Solution Approach 2:
The radar data processing is segmented into multiple stages: first processing range information to identify objects at different distances, then processing Doppler information to determine velocities. This segmentation allows the system to manage large datasets by dividing them into smaller, more manageable chunks that can be processed sequentially with reduced memory requirements.
2Measurement precision
If multiple consecutive measurements are used to extract Doppler effects, then velocity detection accuracy is improved, but the number of data points and processing complexity increase
Solution Approach 1:
The patent segments the processing of multiple consecutive measurements by first organizing data into range bins for each measurement, then systematically processing Doppler information across these organized bins. This structured segmentation reduces processing complexity compared to handling raw consecutive measurements without organization, while still extracting accurate velocity information through Doppler analysis.
3Reliability
If large differences in received power are handled with high bit depth analog to digital conversion, then signal to noise ratio is improved, but data volume and processing requirements increase
Solution Approach 1:
The patent applies different processing approaches to different ranges of received power levels. For strong signals (nearby objects), it uses one processing strategy, while for weak signals (distant objects), it applies another strategy optimized for low signal-to-noise conditions. This local quality approach maintains high reliability across the full dynamic range without uniformly applying high-bit-depth processing to all data, thereby reducing overall data volume and processing requirements.
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 effectively reduces memory requirements and processing power by compressing radar data based on distance and velocity information, allowing for efficient storage and processing of radar signals, thereby enhancing the performance of radar systems in applications like automatic cruise control and blind spot detection.
Implementation Method 1
the round-trip distance that a radar signal travels from a transmitter to an object and back to a receiver can be determined based upon characteristics of the signal
Implementation Method 2
determine a velocity of an object from which the reflections of the transmitted radar signals are received using the Doppler Effect characteristics of the received reflections
Data Source
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AI summary
Aspects of the present disclosure are directed to apparatuses and methods involving the detection of signal characteristics. As may be implemented in accordance with one or more embodiments, an apparatus includes a radar or sonar transceiver that transmits signals and receives reflections of the transmitted signals. A data compression circuit determines a compression factor based on characteristics of the signals, such as may relate to a channel over which the signal passes and/or related aspects of an object from which the signals are reflected (e.g., velocity, trajectory and distance). Data representing the signals is compressed as a function of the determined compression factor.