Davy Dai Huang, 50746 Harvard Ave APT 4, Santa Clara, CA 95051

2021004, Feb 11, 2021

Aug 6, 2019

16/533268

- Sunnyvale CA, US
Davy Huang - Sunnyvale CA, US

G01S 13/93
G06K 9/00
G05D 1/00
G06F 17/14

A method is disclosed for designing a sparse array for an automotive radar. The method moves each of a number of antenna elements to candidate neighboring grid positions starting from an initial random seed placement to iteratively search for a placement of antenna elements that improves upon a cost function. The cost function for each candidate placement may be determined from characteristics of the FFT response associated with the candidate placement. The method may search for a candidate placement with the lowest cost function among the multiple candidate placements based on the random seed placement. The search may be repeated for a large number of random seed placements to find the candidate placement with the lowest cost function corresponding to each random seed placement. The method may compare the lowest cost functions corresponding to the multiple random seed placements to determine an optimized placement having the minimum cost function.

2021004, Feb 11, 2021

Aug 6, 2019

16/533303

- Sunnyvale CA, US
Mei-Li Chi - Sunnyvale CA, US
Davy Huang - Sunnyvale CA, US

G01S 19/29
G01S 13/28
G01S 13/53
G01S 7/292
H01Q 3/01

A method is disclosed for suppressing sidelobes due to artifacts introduced by FFT operations during automotive radar signal processing. Sidelobes of a stronger target from the FFT operations may bury the response from a weaker target when there are multiple targets. The method estimates the sidelobes of an identified target from a measured FFT response and subtracts the estimated sidelobes from the measured FFT response. The identified target may be the strongest target from the measured FFT response. The method estimates the sidelobes to suppress the sidelobes with respect to the peak signal of the identified target. After the estimated sidelobes of the identified target are removed, the updated FFT response may reveal other targets that had been buried. The method may identify additional targets to estimate their sidelobes and may iteratively remove the estimated sidelobes of additional targets from the FFT until a desired sidelobe residual level is achieved.

2021002, Jan 28, 2021

Jul 22, 2019

16/485423

- Sunnyvale CA, US
- Beijing, CN
Xianfei LI - Beijing, CN
Chongchong LI - Beijing, CN
Jian SHENG - Sunnyvale CA, US
Davy HUANG - Sunnyvale CA, US
Manjiang ZHANG - Sunnyvale CA, US

B60W 60/00
G06K 9/00

The disclosure describes various embodiments for online system-level validation of sensor synchronization. According to an embodiment, an exemplary method of analyzing sensor synchronization in an autonomous driving vehicle (ADV) include the operations of acquiring raw sensor data from a first sensor and a second sensor mounted on the ADV, the raw sensor data describing a target object in a surrounding environment of the ADV; and generating an accuracy map based on the raw sensor data in view of timestamps extracted from the raw sensor data. The method further includes the operations of generating a first bounding box and a second bounding box around the target object using the raw sensor data; and performing an analysis of the first and second bounding boxes and the accuracy map using a predetermined algorithm in view of one or more pre-configured sensor settings to determine whether the first sensor and the second sensor are synchronized with each other.

2021002, Jan 21, 2021

Jul 16, 2019

16/513682

- Sunnyvale CA, US
Davy HUANG - Sunnyvale CA, US
Tiffany ZHANG - Sunnyvale CA, US
Dan N. RETTER - Sunnyvale CA, US

H04L 12/40
H04L 12/863
H04L 12/861

In one embodiment, a system for operating an autonomous driving vehicle (ADV) includes a number of modules. These modules include at least a perception module to perceive a driving environment surrounding the ADV and a planning module to plan a path to drive the ADV to navigate the driving environment. The system further includes a bus coupled to the modules and a sensor processing module communicatively coupled to the modules over the bus. The sensor processing module includes a bus interface coupled to the bus, a sensor interface to be coupled to a first set of one or more sensors mounted on the ADV, a message queue to store messages published by the sensors, and a message handler to manage the messages stored in the message queue. The messages may be subscribed by at least one of the modules to allow the modules to monitor operations of the sensors.

2020033, Oct 22, 2020

Apr 16, 2019

16/386068

- Sunnyvale CA, US
SHENGJIN ZHOU - San Jose CA, US
DAVY HUANG - San Jose CA, US
MIN GUO - San Diego CA, US
BERNARD DEADMAN - Austin TX, US

B60W 50/00
G06F 13/42
G05D 1/00
H04L 29/08
H04L 7/00

A method, apparatus, and system for timing synchronization between multiple computing nodes in an autonomous vehicle host system is disclosed. Timing of a first computing node of an autonomous vehicle host system is calibrated based on an external time source. A first timing message is transmitted from the first computing node to a second computing node of the autonomous vehicle host system via a first communication channel between the first computing node and the second computing node. Timing of the second computing node is calibrated based on the first timing message, wherein immediately subsequent to the calibration of timing of the second computing node, timing of the first computing node and of the second computing node is synchronized.

2020006, Feb 27, 2020

Aug 24, 2018

16/112219

- Sunnyvale CA, US
Davy HUANG - Sunnyvale CA, US
Oh KWAN - Sunnyvale CA, US
Tiffany ZHANG - Sunnyvale CA, US

G05D 1/02
G01S 19/13

In one embodiment, a system receives, at a sensor unit, a global positioning system (GPS) pulse signal from a GPS sensor of the autonomous driving vehicle (ADV), where the GPS pulse signal is a RF signal transmitted by a satellite to the GPS sensor, where the sensor unit is coupled to a number of sensors mounted on the ADV to perceive a driving environment surrounding the ADV and to plan a path to autonomously drive the ADV. The system receives a first local oscillator signal from a local oscillator. The system synchronizes the first local oscillator signal to the GPS pulse signal in real-time, including modifying the first local oscillator signal based on the GPS pulse signal. The system generates a second oscillator signal based on the synchronized first local oscillator signal, where the second oscillator signal is used to provide a time to at least one of the sensors.

2018013, May 17, 2018

Nov 16, 2016

15/353555

- Sunnyvale CA, US
JI LI - Sunnyvale CA, US
WENDY LU - Sunnyvale CA, US
ANDREW YAO - Sunnyvale CA, US
JUNWEI BAO - Sunnyvale CA, US
DAVY HUANG - Sunnyvale CA, US

G06F 13/40
G06F 13/42
G06F 1/26

An apparatus includes a chassis housing a control server compartment, a compute server compartment, and an input and output (IO) subsystem compartment. The apparatus further includes an IO subsystem inserted into the IO subsystem compartment, a compute server inserted into the compute server compartment, and a control server inserted into the control server compartment coupled to the compute server via an Ethernet connection. The IO subsystem includes one or more IO modules, where at least some of the IO modules can be coupled to sensors. The compute server receives the sensor data from the IO subsystem via some PCIe links and generates planning and control data based on the sensor data for controlling the autonomous vehicle. The control server controls and operates the autonomous vehicle by sending control commands to hardware of the autonomous vehicle based on the planning and control data received from the compute server.