Microsecond Time-of-Flight Sensor Using Pseudo-Noise Coding
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing LIDAR technologies struggle to accurately detect fast-moving objects in space, especially in noisy environments, due to limitations in signal processing, noise interference, and range ambiguity.
Innovation Solution
The development of a Microsecond Time-of-Flight (μTOF) sensor system that uses a unique arbitrary waveform and pseudo-noise (PN) coding to enhance noise rejection, increase unambiguous range, and allow for simultaneous detection of multiple signals from multiple emitters and detectors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If pulsed LIDAR is used for distance measurement, then the approach is simple and straightforward, but performance degrades significantly in noisy environments and other LIDARs presence
Solution Approach 1:
The patent employs periodic modulation of the light source at specific frequencies, transforming the simple pulsed approach into a frequency-coded periodic signal. This allows the receiver to distinguish the modulated signal from ambient noise through frequency discrimination, thereby maintaining simplicity while improving noise immunity
Solution Approach 2:
The patent changes the temporal parameter of the light signal from simple pulses to frequency-modulated periodic waves. By encoding information in the frequency domain rather than simple time-domain pulses, the system achieves better noise rejection while retaining operational simplicity
2Reliability
If continuous wave (CW) TOF sensors are used, then mutual interference and noise performance improve, but distance ambiguities occur dependent on modulation frequency
Solution Approach 1:
The patent segments the continuous modulation into distinct frequency-coded pulses or chirps. By dividing the continuous wave into discrete, coded segments with unique frequency signatures, the system maintains the noise immunity of CW TOF while eliminating distance ambiguities through segment identification
Solution Approach 2:
The patent introduces frequency coding as an intermediary layer between the continuous wave modulation and distance measurement. This frequency code acts as a mediator that carries unique identification information, allowing the system to resolve distance ambiguities while maintaining continuous wave operation benefits
3Device complexity
If detector arrays for CWTOF are used, then cost, size, and power scale better, but sample rates are limited by array readout times and integration times
Solution Approach 1:
The patent uses periodic frequency-coded modulation that allows for faster integration times. The coded periodic structure enables more rapid signal processing and shorter integration periods, thereby increasing the effective sample rate while maintaining array scalability benefits
Solution Approach 2:
The patent changes the integration time parameter by using frequency-coded signals that can be processed more rapidly through correlation or FFT-based methods. This reduces the effective integration time required per sample, increasing sample rate while preserving the cost and size scaling advantages of array architectures
4Ease of manufacture
If pulsed LIDAR is used, then distance measurement is straightforward, but walk error occurs due to finite pulse rise times
Solution Approach 1:
The patent replaces simple pulses with periodic frequency-modulated waves. The periodic nature with well-defined frequency transitions provides sharper temporal features for accurate time-of-flight measurement, eliminating walk error while keeping the measurement approach straightforward
Solution Approach 2:
The patent changes from time-domain pulse width parameters to frequency-domain modulation parameters. This transformation eliminates the walk error inherent in finite-rise-time pulses by using frequency transitions that provide more precise temporal localization through zero-crossing or phase detection methods
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 μTOF sensor system achieves significant improvements in noise immunity, sensitivity, and range, enabling accurate detection of fast-moving objects at extended distances, even in challenging ambient conditions.
Implementation Method 1
Distance can be calculated by measuring the time of flight for the light to travel to the object and back
Implementation Method 2
uses sensor technology employed by modern cell phones and GPS to pull weak signals from multiple sources in a noisy environment
Data Source
AI summary
An example μTOF is a flexible, small, sensor unit that uses modulated light to measure distance. The architecture of the sensor allows for many use cases. Use cases include the classic single emitter, single detector topology, but also include capability for operability as a full multi-input, multi-output (MIMO) system. In a MIMO configuration, the emitters and detectors can be arranged in a configuration similar to an RF antenna array or any number of other configurations from a single emitter/detector pair to vast dispersions of emitters and detectors. By coding the signal output by each emitter with a unique pseudo-noise (PN) or similar sequence, reflected signals received at the detector can be separated from each other, providing path distances between each emitter-detector pair. Given the robustness and noise immunity of PN sequences, this approach works well even with signal levels well below the noise floor. Using the measured path distances from each sensor to each emitter, the locations of objects in the scene can be extracted by triangulation.