High-Range, Low-Power LiDAR Detection via Digital Correlation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing LiDAR systems face challenges in achieving high range and low power consumption while maintaining electro-optical efficiency, as increasing peak power of optical signals often degrades efficiency and conventional detectors struggle to reliably detect weak return signals.
Innovation Solution
The use of wavelength-locked multi-mode laser diodes and advanced digital signal processing techniques, including digitization and correlation detection, to enhance the signal-to-noise ratio and improve the detection of weak optical signals, allowing for increased range and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Length of stationary object
If the peak power of optical signals is increased to extend detection range, then the detection range is improved, but electro-optical efficiency deteriorates
Solution Approach 1:
The system transmits optical signals in periodic pulses rather than continuously. By using pulsed transmission with appropriate duty cycles, the system achieves high peak power for extended range while maintaining low average power consumption, thus resolving the contradiction between detection range and electro-optical efficiency.
Solution Approach 2:
The system dynamically adjusts transmission parameters including pulse width, pulse frequency, and peak power level based on detection requirements. This parameter optimization allows the system to achieve high peak power for extended range detection while maintaining acceptable average power consumption and electro-optical efficiency.
2Device complexity
If conventional detectors are used to detect weak return signals, then device complexity is reduced, but measurement precision deteriorates
Solution Approach 1:
The system replaces conventional analog detection mechanisms with digital signal processing techniques. By converting the detected signal to digital form and applying correlation detection algorithms, the system achieves high measurement precision for weak signals while maintaining relatively simple hardware architecture.
Solution Approach 2:
The system creates a digital copy of the transmitted optical signal pattern and uses correlation detection to compare it with the received signal. This copying approach enables precise detection of weak return signals by matching patterns rather than relying solely on signal amplitude, improving measurement precision without significantly increasing device complexity.
3Productivity
If multiple channels are used to increase pixel count, then productivity is improved, but device complexity increases
Solution Approach 1:
The system combines multiple channels into a unified processing architecture where all channels share common components such as the pulsed transmission system, timing synchronization mechanism, and digital signal processing unit. This merging approach increases productivity by enabling multi-channel operation while minimizing the complexity increase through shared resources.
Solution Approach 2:
The system designs a universal transmission and processing platform that can operate with varying numbers of channels. The same pulsed transmission system, timing control, and digital processing infrastructure support single-channel or multi-channel configurations, allowing the system to achieve high pixel generation rates without proportionally increasing overall system complexity.
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 enables LiDAR systems to detect return signals containing as few as 5 to 7 photons, extending the detection range up to 4.5 to 7 times further than conventional systems and improving electro-optical efficiency, while maintaining current performance levels.
Implementation Method 1
a photodetector configured to detect a return signal and generate a captured signal representing the return signal
Implementation Method 2
the return signal includes a portion of the optical signal reflected by a surface in an environment of the LIDAR system
Data Source
AI summary
A LIDAR system may include a transmitter, a photodetector, and a receiver. The receiver may transmit an optical signal having a signature. The photodetector may detect a return signal and generate a captured signal representing the return signal. The receiver may process the captured signal to determine a propagation time of the optical signal between the transmitter and the surface. The receiver may include signal processing components and timing circuitry. The signal processing components may digitize the captured signal and determine whether a signature of the digitized signal matches the signature of the optical signal. The timing circuitry may determine the propagation time of the optical signal between the transmitter and the surface based on the digitized signal when the signature of the digitized signal is determined to match the signature of the optical signal.