Lidar Frequency Analysis Segmentation
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Solution Overview
Problem
Conventional LIDAR systems face challenges in accurately detecting objects at long distances or with low reflectance due to low signal-to-noise ratios, leading to reduced resolution and inaccurate positioning, especially when measurement time is extended.
Innovation Solution
A LIDAR device with a transmission unit that transmits modulated waves, a scanning unit, a reception unit, a data conversion unit, and frequency analysis units that generate ranging point data by performing frequency analysis on multiple data sets with varying angle ranges, allowing for high sensitivity and resolution detection by adjusting sampling intervals and readout angles based on peak intensity and frequency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If measurement time is extended to detect objects with low SN ratios, then detection sensitivity is improved, but resolution deteriorates and positioning becomes inaccurate
Solution Approach 1:
The patent segments the angular range into multiple first angle ranges and further divides each into multiple second angle ranges. By performing frequency analysis on sampling data within these segmented angular ranges, the system can detect objects with low SN ratios while maintaining resolution. The segmentation allows parallel processing of multiple data sets, improving detection sensitivity without compromising resolution.
Solution Approach 2:
The patent introduces a new dimension of analysis by performing frequency analysis not only on the entire angular range but also on segmented angular ranges. This multi-dimensional approach enables simultaneous improvement of detection sensitivity (through comprehensive frequency analysis) and resolution (through angular range segmentation), resolving the contradiction between these two parameters.
2Reliability
If frequency analysis is performed on all sampling data, then detection coverage is improved, but processing time increases
Solution Approach 1:
The patent segments the sampling data into multiple data sets based on different angular ranges (first angle ranges and second angle ranges). By performing frequency analysis on these segmented data sets in parallel, the system achieves comprehensive detection coverage while reducing processing time. The segmentation enables concurrent processing of multiple data portions, maintaining detection coverage without the time penalty of sequential analysis.
Solution Approach 2:
The patent performs frequency analysis on partial data sets (sampling data within specific angular ranges) rather than requiring analysis of all sampling data. This partial action approach maintains sufficient detection coverage for objects within the scanned angular range while significantly reducing processing time. The excessive action is avoided by analyzing only the necessary portions of data.
3Device complexity
If sampling interval is fixed, then system simplicity is maintained, but adaptability to different distances and reflectance is reduced
Solution Approach 1:
The patent makes the sampling interval dynamic by adjusting it based on the angular range being analyzed. Different sampling intervals are used for different first angle ranges and second angle ranges, allowing the system to adapt to objects at different distances and with different reflectance properties. This dynamic adjustment maintains system simplicity while significantly improving adaptability.
Solution Approach 2:
The patent changes the sampling interval parameter according to the analysis requirements of different angular ranges. By varying this parameter, the system can optimize detection performance for objects at different distances and with different reflectance, maintaining simplicity while achieving high adaptability to various detection scenarios.
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 detection of objects with low SN ratios with high sensitivity and high-resolution detection of objects with high SN ratios, reducing the decrease in sensitivity and resolution, and improving processing performance by parallel frequency analysis across multiple data sets.
Implementation Method 1
measuring a distance to an object by using a phase difference between a continuous wave transmitted and modulated with passage of time and a reflected wave reflected from the object
Data Source
AI summary
A LIDAR device includes a transmission unit, a scanning unit, a reception unit, a data conversion unit, a data holding unit, a frequency analysis unit configured to execute frequency analysis to acquire ranging point data, and a point group generator configured to generate a group of ranging points acquired by using a result of frequency analysis on a first analysis target data set and a group of ranging points acquired by using a result of frequency analysis on a second analysis target data set.