Michael Andrew Hamilton

US Patent:

20220390582, Dec 8, 2022

Filed:

Jun 3, 2021

Appl. No.:

17/337614

Inventors:

- San Diego CA, US
Radhika Dilip GOWAIKAR - San Diego CA, US
Makesh Pravin JOHN WILSON - San Diego CA, US
Amin ANSARI - San Diego CA, US
Michael John HAMILTON - San Diego CA, US
Shantanu Chaisson SANYAL - San Diego CA, US
Sundar SUBRAMANIAN - San Diego CA, US

International Classification:

G01S 13/42
G01S 7/03
G01S 13/931

Abstract:

In some aspects, a system may receive, from a first one-dimensional radar array, first information based at least in part on first reflections associated with an azimuthal plane. The system may further receive, from a second one-dimensional radar array, second information based at least in part on second reflections associated with an elevation plane. Accordingly, the system may detect an object based at least in part on the first information and may determine an elevation associated with the object based at least in part on the second information. Numerous other aspects are described.

US Patent:

20220357441, Nov 10, 2022

Filed:

May 10, 2021

Appl. No.:

17/316223

Inventors:

- San Diego CA, US
Sundar SUBRAMANIAN - San Diego CA, US
Radhika Dilip GOWAIKAR - San Diego CA, US
Ahmed Kamel SADEK - San Diego CA, US
Makesh Pravin JOHN WILSON - San Diego CA, US
Volodimir SLOBODYANYUK - San Diego CA, US
Shantanu Chaisson SANYAL - San Diego CA, US
Michael John HAMILTON - San Diego CA, US

International Classification:

G01S 13/86
G01S 13/89
G06T 7/521
G06N 20/00
G06T 7/11

Abstract:

A device for processing image data is disclosed. The device can obtain a radar point cloud and one or more frames of camera data. The device can determine depth estimates of one or more pixels of the one or more frames of camera data. The device can generate a pseudo lidar point cloud using the depth estimates of the one or more pixels of the one or more frames of camera data, wherein the pseudo lidar point cloud comprises a three-dimensional representation of at least one frame of the one or more frames of camera data. The device can determine one or more object bounding boxes based on the radar point cloud and the pseudo lidar point cloud.

US Patent:

20230086818, Mar 23, 2023

Filed:

Sep 21, 2021

Appl. No.:

17/480570

Inventors:

- San Diego CA, US
Ahmed Kamel SADEK - San Diego CA, US
Amin ANSARI - Kirkland WA, US
Sundar SUBRAMANIAN - San Diego CA, US
Radhika Dilip GOWAIKAR - San Diego CA, US
Makesh Pravin JOHN WILSON - San Diego CA, US
Michael John HAMILTON - San Diego CA, US
Shantanu Chaisson SANYAL - San Diego CA, US

International Classification:

B60R 11/04
H04N 5/232

Abstract:

System and method for processing a camera frame in a mobile device by partitioning the camera frame into different sections based on the distance from a vehicle to each of the sections and the required resolution of each of the sections. A mobile device comprises: a memory; a processor communicatively coupled to the memory, the processor configured to: receive a camera frame from a camera mounted on a vehicle traveling on a road; determine a drivable path of the vehicle; project the drivable path onto the camera frame; partition a part of the camera frame containing the drivable path into at least one section based on a distance from the vehicle to each of the at least one section; and determine a required resolution of each of the at least one section based on the distance from the vehicle to each of the at least one section.

US Patent:

20210255304, Aug 19, 2021

Filed:

Nov 27, 2019

Appl. No.:

16/698870

Inventors:

- San Diego CA, US
Amin ANSARI - San Diego CA, US
Bence MAJOR - Amsterdam, NL
Ravi Teja SUKHAVASI - La Jolla CA, US
Radhika Dilip GOWAIKAR - San Diego CA, US
Xinzhou WU - San Diego CA, US
Sundar SUBRAMANIAN - San Diego CA, US
Michael John HAMILTON - San Diego CA, US

International Classification:

G01S 13/60
G01S 7/02
G01S 7/41
G01S 17/931

Abstract:

Disclosed are techniques for employing deep learning to analyze radar signals. In an aspect, an on-board computer of a host vehicle receives, from a radar sensor of the vehicle, a plurality of radar frames, executes a neural network on a subset of the plurality of radar frames, and detects one or more objects in the subset of the plurality of radar frames based on execution of the neural network on the subset of the plurality of radar frames. Further, techniques for transforming polar coordinates to Cartesian coordinates in a neural network are disclosed. In an aspect, a neural network receives a plurality of radar frames in polar coordinate space, a polar-to-Cartesian transformation layer of the neural network transforms the plurality of radar frames to Cartesian coordinate space, and the neural network outputs the plurality of radar frames in the Cartesian coordinate space.

US Patent:

20210208247, Jul 8, 2021

Filed:

Sep 23, 2020

Appl. No.:

17/029722

Inventors:

- San Diego CA, US
Volodimir SLOBODYANYUK - San Diego CA, US
Sundar SUBRAMANIAN - San Diego CA, US
Radhika Dilip GOWAIKAR - San Diego CA, US
Michael John HAMILTON - San Diego CA, US
Amin ANSARI - San Diego CA, US

International Classification:

G01S 7/41
G01S 13/52
G06T 3/40

Abstract:

Embodiments provided herein allow for identification of one or more regions of interest in a radar return signal that would be suitable for selected application of super-resolution processing. One or more super-resolution processing techniques can be applied to the identified regions of interest. The selective application of super-resolution processing techniques can reduce processing requirements and overall system delay. The output data of the super-resolution processing can be provided to a mobile computer system. The output data of the super-resolution processing can also be used to reconfigure the radar radio frequency front end to beam form the radar signal in region of the detected objects. The mobile computer system can use the output data for implementation of deep learning techniques. The deep learning techniques enable the vehicle to identify and classify detected objects for use in automated driving processes. The super-resolution processing techniques can be implemented in analog and/or digital circuitry.

US Patent:

20210152245, May 20, 2021

Filed:

Nov 20, 2019

Appl. No.:

16/689952

Inventors:

- San Diego CA, US
Michael John HAMILTON - San Diego CA, US

International Classification:

H04B 10/25
H04L 29/08
H04L 7/00
G01S 7/00
G01S 7/40
G01S 13/931

Abstract:

Apparatus and methods are disclosed for communicating between distributed automotive sensors, including radar sensors, wherein sensors transmit a synchronization (SYNC) signal, each SYNC signal transmitted via a substantially equal-length fiber optic link corresponding with each sensor. A central node receives the SYNC signals via the fiber optic links corresponding with each of the sensors and determines a master SYNC signal based on the received SYNC signals. The central node then transmits the master SYNC signal via the fiber optic links to the sensors, which receive the master SYNC signal and transmit, via fiber optic link, sensor data synchronized in accordance with the master SYNC signal. The synchronized sensor data are received at the central node and coherently aggregated, and transmitted to a compute node for post-processing. For radar data, the post-processing may include determination of an angular position of an object within detection range of at least two radar sensors.

US Patent:

20200025865, Jan 23, 2020

Filed:

May 15, 2019

Appl. No.:

16/413354

Inventors:

- San Diego CA, US
Junyi LI - Chester NJ, US
Sundar SUBRAMANIAN - San Diego CA, US
Michael John HAMILTON - San Diego CA, US

International Classification:

G01S 7/02
G01S 13/04
H04L 7/06
H04B 7/0456
H04B 1/69

Abstract:

Certain aspects of the present disclosure provide techniques for radar detection by an apparatus. In certain aspects a method for radar detection by an apparatus includes selecting one or more radar transmission parameters based on a reference time, wherein the reference time is common to at least a group of vehicles. The method further includes performing radar detection using the selected radar transmission parameters and the reference time.

US Patent:

20200025866, Jan 23, 2020

Filed:

Jun 11, 2019

Appl. No.:

16/437092

Inventors:

- San Diego CA, US
Junyi LI - Chester NJ, US
Sundar SUBRAMANIAN - San Diego CA, US
Michael John HAMILTON - San Diego CA, US

International Classification:

G01S 7/02

Abstract:

Certain aspects provide a method for radar detection by an apparatus. The method generally includes transmitting a radar waveform in sets of transmission time intervals (TTIs), using a common set of radar transmission parameters in each set of TTIs, to perform detection of a target object, varying at least one of the common set of radar transmission parameters between sets of TTIs, and identifying interfering signals based on observed changes in monitored parameters of received signals across sets of TTIs due to the varying.