Stmicroelectronics Gmbh

Stmicroelectronics S.r.l.

Csr Technology Holdings Inc.

Stmicroelectronics International N.v.

Csr Technology Inc.

Stmicroelectronics (grand Ouest) Sas

Stmicroelectronics (grenoble 2) Sas

Mahaveer Jain

Mahesh Chowdhary

Arun Kumar

Roberto Mura

Nicola Matteo Palella

Leonardo Colombo

Manish Sharma

Stefano Paolo Rivolta

Sankalp Dayal

Ashish Bhargava

Kolin Paul

Gagan Narula

Ashutosh Pande

Andrea Donadel

Chinmay Agarwal

Joëlle Philippe

A device including microelectromechanical systems (MEMS) sensors are used in dead reckoning in conditions where Global Positioning System (GPS) signals or Global Navigation Satellite System (GNSS) signals are lost. The device is capable of tracking the location of the device after the GPS/GNSS signals are lost by using MEMS sensors such as accelerometers and gyroscopes. By calculating a misalignment angle between a forward axis of a sensor frame of the device and a forward axis of a vehicle frame using the data received from the MEMS sensors, the device can accurately calculate the location of a user or the vehicle of the device even without the GPS/GNSS signals. Accordingly, a device capable of tracking the location of the user riding in the vehicle in GPS/GNSS signals absent environment can be provided.

Inertial navigation system capable of dead reckoning in vehicles

The present disclosure is directed to a device and method for detection of motion events including towing of the vehicle, jacking of the vehicle, and the vehicle being hit by another object. Processing is split between an MCU and a sensor unit. After the vehicle is turned off and before the MCU enters a sleep mode, the MCU calculates a gravity vector of the vehicle using accelerometer data, calculates threshold values based on the gravity vector, and saves the threshold values. After the MCU enters the sleep mode, the sensor unit subsequently monitors and detects motion events with the saved threshold values.

Motion event detection

A system includes inertial sensors and a GPS. The system generates a first estimated vehicle velocity based on motion data and positioning data, generates a second estimated vehicle velocity based on the processed motion data and the first estimated vehicle velocity, and generates fused datasets indicative of position, velocity and attitude of a vehicle based on the processed motion data, the positioning data and the second estimated vehicle velocity. The generating the second estimated vehicle velocity includes: filtering the motion data, transforming the filtered motion data in a frequency domain based on the first estimated vehicle velocity, generating spectral power density signals, generating an estimated wheel angular frequency and an estimated wheel size based on the spectral power density signals, and generating the second estimated vehicle velocity as a function of the estimated wheel angular frequency and the estimated wheel size.

Method for motion estimation in a vehicle, corresponding device and computer program product

An electronic device includes a magnetometer that outputs magnetometer sensor signals and a gyroscope that outputs gyroscope sensor signals. The electronic device includes a magnetometer calibration module that calibrates the magnetometer utilizing the gyroscope sensor signals. The electronic device generates a first magnetometer calibration parameter based on a Kalman filter process. The electronic device generates a second magnetometer calibration parameter based on a least squares estimation process.

System and method for fast magnetometer calibration using gyroscope

Digital signal processing circuitry, in operation, determines, based on accelerometer data, a carry-position of a device. Double-tap detection parameters are set using the determined carry-position. Double-taps are detected using the set double-tap detection parameters. In response to detection of a double-tap, control signals, such as a flag or an interrupt signal, are generated and used to control operation of the device. For example, a device may enter a wake mode of operation in response to detection of a double-tap.

Double-tap event detection device, system and method

A device including microelectromechanical systems (MEMS) sensors is used in dead reckoning in conditions where Global Positioning System (GPS) signals or Global Navigation Satellite System (GNSS) signals are lost. The device is capable of tracking the location of the device after the GPS/GNSS signals are lost by using MEMS sensors such as accelerometers and gyroscopes. By calculating a misalignment angle between a sensor frame of the device with either the movement direction of the vehicle or the walking direction of a pedestrian using the MEMS sensors, the device can accurately calculate the location of a user of the device even without the GPS/GNSS signals. Accordingly, a device capable of tracking the location of a pedestrian and a user riding in a vehicle without utilizing GPS/GNSS signals can be provided.

Dead reckoning by determining misalignment angle between movement direction and sensor heading direction

A portable device includes one or more memories and travel mode control circuitry coupled to the one or more memories. The travel mode control circuitry, in operation, monitors motion data and detects a first travel state of the device based on the monitored motion data and an acceleration profile. When the first travel state of the device is detected, motion data and pressure data are monitored to detect a transition from the first travel state to a second travel state of the device. When the transition to the second travel state of the device is detected, one or more control signals are generated to cause the device to enter a first travel mode of operation.

Mobile device transportation mode management device, system and method

A system may include a motion sensor configured to generate a motion signal in response to a movement of an electronic device, and at least one feature detection circuit configured to determine at least one metric based on the motion signal. The system may further include a classifying circuit configured to determine whether the electronic device is in contact with a human body based on the at least one metric.

System and method of determining whether an electronic device is in contact with a human body

A portable device includes one or more memories and travel mode control circuitry coupled to the one or more memories. The travel mode control circuitry, in operation, monitors motion data and temperature data to detect a first travel state of the device. When the first travel state of the device is detected, motion data and pressure data are monitored to detect a transition from the first travel state to a second travel state of the device. When the transition to the second travel state of the device is detected, one or more control signals are generated to cause the device to enter a first travel mode of operation.

In general, the invention relates to an algorithm and process for automated and/or continuous calibration of magnetic sensor, for example such as a sensor installed in a mobile positioning system handset. According to certain aspects, the calibration process can use the normal motion of the handset such that all measurement data from the three orthogonal axes of sensor when exposed to Earth's magnetic field is collected. According to still further aspects, the process includes fitting measurement data to an ellipsoid that characterizes the actual magnetic field measurements from a magnetic sensor, so that anomalies such as hard iron effect, soft iron effect and scale factors can be extracted and/or corrected by comparison to a sphere represented by magnetic field data from a model at the sensor's location.

Method and apparatus for calibrating a magnetic sensor

The present invention relates generally to position determination, and more particularly to methods and apparatuses to determine the walking direction (heading of a user) using MEMS inertial sensors commonly found in mobile devices such as cellphones. According to some aspects, the invention includes a methodology to allow the walking angle to be determined dynamically. In embodiments, the methodology includes pattern matching accelerometer measurement data to a reference acceleration pattern.

Method and apparatus for determining walking direction for a pedestrian dead reckoning process

A method includes acquiring magnetic data from a magnetometer, processing the magnetic data to perform robust calibration, and generating optimum calibration parameters using a calibration status indicator. To that end, the method includes generating a calibration status indicator as a function of time elapsed since a last calibration and variation in total magnetic field in previously stored magnetic data, detecting anomalies, and extracting a sparse magnetic data set using comparison between the previously stored magnetic data and the magnetic data. Calibration parameters are generated for the magnetometer using a calibration method as a function of the magnetic data set. The calibration parameters are stored based on performing a validation and stability check on the calibration parameters, and weighted with the previously stored calibration parameters to produce weighted calibration parameters. Calibration settings are generated as a function of the weighted calibration parameters, if the weighted calibration parameters were produced.

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Santa Clara, CA, United States of America

Mahaveer Jain