Device and method for processing a histogram of arrival times in an optical sensor

Patent metadata

Field	Value
Publication number	US-10796191-B2
Application number	US-201816142544-A
Country	US
Kind code	B2
Filing date	Sep 26, 2018
Priority date	Sep 26, 2018
Publication date	Oct 6, 2020
Grant date	Oct 6, 2020

Abstract

An example device has optical emitters for emitting incident radiation within a field of view and optical detectors for receiving reflected radiation. Based on the incident radiation and the reflected radiation, a histogram indicative of a number of photon events that are detected by the optical detectors over time bins is generated. The time bins is indicative of time differences between emission of the incident radiation and reception of the reflected radiation. The device further includes; a processor programmed to iteratively process the histogram by executing an expectation-maximization algorithm to detect a presence of objects located in the field of view of the device.

First claim

What is claimed is:

1. A device, comprising:
a plurality of optical emitters configured to emit incident radiation within a field of view of the device;
a plurality of optical detectors configured to receive reflected radiation and to generate a histogram based on the incident radiation and the reflected radiation, the histogram being indicative of a number of photon events detected by the plurality of optical detectors over a plurality of time bins, the plurality of time bins being indicative of a plurality of time differences between emission of the incident radiation and reception of the reflected radiation; and
a processor programmed to iteratively process the histogram by executing an expectation-maximization algorithm to detect a presence of objects located in the field of view of the device.

2. The device of claim 1 , wherein executing the expectation-maximization algorithm to detect the presence of objects located in the field of view of the device comprises executing the expectation-maximization algorithm to detect a number of objects located in the field of view of the device.

3. The device of claim 1 , wherein executing the expectation-maximization algorithm to detect the presence of objects located in the field of view of the device comprises:
selecting a respective initial pulse proportion, a respective initial pulse center, and a respective initial spread factor for each of a first number of parametrizable pulse shapes;
updating a respective pulse proportion for each of the first number of parametrizable pulse shapes based on the respective initial pulse center and the respective initial spread factor;
updating a respective pulse center and a respective spread factor for each of the first number of parametrizable pulse shapes based on the respective pulse proportion;
determining a respective likelihood associated with the respective pulse center and the respective spread factor for each of the first number of parametrizable pulse shapes; and
determining whether a first convergence criterion has been satisfied.

4. The device of claim 3 , wherein determining whether the first convergence criterion has been satisfied comprises:
determining a likelihood difference between the respective likelihood of a current iteration of the expectation-maximization algorithm and the respective likelihood of a most-previous current iteration of the expectation-maximization algorithm; and
determining whether the first convergence criterion has been satisfied based on the likelihood difference.

5. The device of claim 4 , wherein determining whether the first convergence criterion has been satisfied based on the likelihood difference comprises:
determining that the first convergence criterion has been satisfied in response to the likelihood difference being negative for a predetermined number of consecutive iterations of the expectation-maximization algorithm.

6. The device of claim 4 , wherein determining whether the first convergence criterion has been satisfied based on the likelihood difference comprises:
determining that the first convergence criterion has been satisfied in response to the likelihood difference being less than a first threshold.

7. The device of claim 3 , further comprising:
in response to a determination that the first convergence criterion has not been satisfied, designating the respective pulse proportion, the respective pulse center, and the respective spread factor as the respective initial pulse proportion, the respective initial pulse center, and the respective initial spread factor for each of the first number of parametrizable pulse shapes; and
repeating an update of the respective pulse proportion, the respective pulse center, and a respective spread factor for each of a first number of parametrizable pulse shapes.

8. The device of claim 3 , further comprising:
in response to a determination that the first convergence criterion has been satisfied, selecting the respective pulse proportion, the respective pulse center, and the respective spread factor of a most-recent iteration of the expectation-maximization algorithm as respective pulse parameters for each of the first number of parametrizable pulse shapes; and
determining whether a second convergence criterion has been satisfied based on the respective likelihood associated with the respective pulse parameters.

9. The device of claim 8 , wherein determining whether the second convergence criterion has been satisfied comprises:
determining a log likelihood function based on the respective likelihood associated with the respective pulse parameters;
determining a score based on the log likelihood function; and
determining that the second convergence criterion has been satisfied in response to the score being less than a second threshold.

10. The device of claim 8 , further comprising:
incrementing the first number of parametrizable pulse shapes to generate a second number of parametrizable pulse shapes in response to a determination that the second convergence criterion has not been satisfied;
selecting a respective initial pulse proportion, a respective initial pulse center, and a respective initial spread factor for each of the second number of parametrizable pulse shapes;
updating a respective pulse proportion for each of the second number of parametrizable pulse shapes based on the respective initial pulse center and the respective initial spread factor;
updating a respective pulse center and a respective spread factor for each of the second number of parametrizable pulse shapes based on the respective pulse proportion;
determining a respective likelihood associated with the respective pulse center and the respective spread factor for each of the second number of parametrizable pulse shapes; and
determining whether the first convergence criterion has been satisfied.

11. The device of claim 8 , further comprising detecting the presence of objects located in the field of view of the device based on the respective pulse proportion, the respective pulse center, and the respective spread factor in response to a determination that the second convergence criterion has been satisfied.

12. The device of claim 1 , wherein the plurality of optical detectors comprises at least one of photo diodes, avalanche photo diodes, or single-photon avalanche diodes.

13. The device of claim 1 , wherein the plurality of optical emitters comprises at least one of vertical-cavity surface-emitting lasers, quantum well lasers, quantum cascade lasers, inter-band cascade lasers, or vertical external-cavity surface-emitting lasers.

14. The device of claim 1 , wherein the plurality of optical emitters are configured for at least one of continuous wave operation, quasi-continuous wave operation, or pulsed operation.

15. A method, comprising:
emitting incident radiation using a plurality of optical emitters of a sensor device;
receiving reflected radiation using a plurality of optical detectors from one or more objects located in a field of view of the sensor device;
generating, by a processor, a histogram based on the incident radiation and the reflected radiation, the histogram being indicative of a number of photon events detected by the plurality of optical detectors over a plurality of time bins, the plurality of time bins being indicative of a plurality of time differences between emission of the incident radiation and reception of the reflected radiation; and
iteratively processing the histogram by executing an expectation-maximization algorithm to determine a number of the one or more objects located in the field of view of the sens

Assignees

• St Microelectronics Sa
• St Microelectronics Res & Dev Ltd

Inventors

• De Salivet De Fouchecour Francois
• Mcleod Stuart
• Baxter Donald
• Pothier Olivier
• Lebihen Thierry

Classifications

• G01S7/4815 Primary

  using multiple transmitters · CPC title

• G06T7/521

  from laser ranging, e.g. using interferometry; from the projection of structured light · CPC title

• G01S7/4876

  by removing unwanted signals (G01S7/495 takes precedence) · CPC title

• G06T2207/10028

  Range image; Depth image; 3D point clouds · CPC title

• G06T2207/20072

  Graph-based image processing · CPC title