Real-Time Probability Functions for Geiger-Mode LiDAR Noise Filtering
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Solution Overview
Problem
Conventional Geiger mode LiDAR systems suffer from high computational demands for real-time noise filtering due to continuously triggering detectors, leading to suboptimal signal-to-noise ratios.
Innovation Solution
Applying probability functions in real-time using a multiplier and circular shift register to filter background noise, improving signal-to-noise ratio by subtracting likely noise sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If Geiger mode detectors operate continuously to detect reflected light, then detection capability is improved, but computational load and processing power requirements increase significantly
Solution Approach 1:
The system pre-calculates and stores probability functions that represent expected noise patterns in lookup tables before real-time operation. During actual LiDAR operation, these pre-computed probability functions are directly applied to filter detected photons, eliminating the need for complex real-time noise analysis and significantly reducing computational load while maintaining detection reliability
Solution Approach 2:
Probability functions serve as an intermediary layer between the raw detector output and the final distance calculation. These functions model the statistical behavior of noise and enable selective filtering of false photon detections without requiring full computational processing of every detected signal, thus reducing power consumption while preserving detection accuracy
2Measurement precision
If probability functions are applied in real-time using lookup tables, then noise filtering performance is improved, but memory requirements and data storage increase
Solution Approach 1:
The system varies the resolution and granularity of the lookup tables based on operational requirements. By adjusting parameters such as time-bin resolution and probability function complexity, the system optimizes the balance between noise filtering performance and memory consumption, allowing adaptive allocation of storage resources
Solution Approach 2:
The implementation uses simplified probability function representations in lookup tables that consume minimal memory but provide sufficient filtering performance for real-time operation. Rather than storing comprehensive noise models, the system uses compact probabilistic representations that can be rapidly applied and discarded each measurement cycle
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
Enhances signal-to-noise ratio and reduces computational load for real-time data processing, enabling efficient noise removal and improved image processing performance.
Implementation Method 1
The term 'Geiger mode' refers to an application of a bias voltage which exceeds the breakdown voltage of the APD. When the APD is over biased, the detector operates in a metastable state where a single photon may cause an avalanche current.
Implementation Method 2
a single photon may cause an avalanche current
Data Source
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AI summary
A method for applying probability functions in real time includes receiving an input value. An optimized binary sequence is selected from a lookup table based on the received input value. The lookup table includes probability values of at least a part of a noise probability sequence. The input value is masked by a least significant bit of the selected optimized binary sequence to yield an output value. The selected optimized binary sequence is right shifted by one bit and the right shifted bit is carried over to a most significant bit position of the selected optimized binary sequence.