Laser Range Finder Dynamic Threshold Signal Selection
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Solution Overview
Problem
Current laser range finders inaccurately select return laser signals associated with targets due to heuristic approaches that fail to account for range and atmospheric losses.
Innovation Solution
A laser range finder system that includes a processor to compare the amplitude of each return laser signal with a range varying threshold, accounting for range and atmospheric losses, to accurately determine the signal associated with the target.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If heuristic approaches are used to select return laser signals, then the device complexity is reduced and ease of operation is improved, but the measurement precision and reliability deteriorate
Solution Approach 1:
The system performs self-characterization by automatically measuring atmospheric losses and range variations, then uses this self-acquired data to dynamically adjust selection thresholds. The LRF characterizes the environment itself and uses that characterization to improve signal selection accuracy without requiring external calibration or complex manual setup.
Solution Approach 2:
The invention dynamically changes the selection threshold parameter based on measured atmospheric conditions and range. Instead of using a fixed heuristic threshold, the system adjusts the threshold parameter in real-time according to environmental factors such as atmospheric loss and range variations, thereby maintaining high measurement precision across different operating conditions.
2Reliability
If fixed threshold approaches are used for signal selection, then the device complexity is reduced, but the reliability and adaptability deteriorate due to inability to account for range and atmospheric losses
Solution Approach 1:
The system performs preliminary characterization of the measurement environment by measuring atmospheric loss and range variations before conducting the actual signal selection. This preliminary action establishes baseline data that is then used to adjust selection criteria, ensuring reliable performance from the start of each measurement sequence.
Solution Approach 2:
The system implements feedback by continuously monitoring atmospheric conditions and range measurements, then using this information to dynamically adjust the signal selection threshold. The measured environmental parameters feed back into the selection algorithm, creating a closed-loop system that adapts to changing conditions and maintains high reliability.
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 system provides accurate identification of the return laser signal associated with the target by using a dynamic thresholding module that accounts for varying conditions, ensuring precise selection and display of the correct amplitude.
Implementation Method 1
A laser range finder (LRF) emits a laser beam towards a target
Implementation Method 2
receives multiple return laser signals reflected from objects including the target
Data Source
AI summary
A laser range finder (LRF) and an automated method for determining a return laser signal associated with a target thereof are disclosed. In one example embodiment, the LRF includes a laser beam emitter to emit a laser beam towards a target. Further, the LRF includes a receiver circuit to receive multiple return laser signals reflected from objects including the target and to determine an amplitude of each of the multiple return laser signals. Furthermore, the LRF includes a processor coupled to the receiver circuit to compare the amplitude of each of the multiple return laser signals with a range varying threshold that accounts for range and atmospheric losses and to determine one of the multiple return laser signals as being associated with the target based on the comparison.