Texas Instruments Corporation

Sachin Bhardwaj

Sriram Murali

Karthik Subburaj

Karthik Ramasubramanian

Jaiganesh Balakrishnan

Brian Paul Ginsburg

Sandeep Rao

Jayawardan Janardhanan

Sthanunathan Ramakrishnan

Pankaj Gupta

Goutam Dutta

Yogesh Shekar

A frequency modulated continuous wave (FMCW) radar system is provided that includes a receiver configured to generate a digital intermediate frequency (IF) signal, and an interference monitoring component coupled to the receiver to receive the digital IF signal, in which the interference monitoring component is configured to monitor at least one sub-band in the digital IF signal for interference, in which the at least one sub-band does not include a radar signal.

Interference detection in a frequency modulated continuous wave (FMCW) radar system

The disclosure provides a radar apparatus for estimating a position and a velocity of the plurality of obstacles. The radar apparatus includes a local oscillator that generates a first signal. A first transmit unit receives the first signal from the local oscillator and generates a first transmit signal. A frequency shifter receives the first signal from the local oscillator and generates a second signal. A second transmit unit receives the second signal and generates a second transmit signal. The frequency shifter provides a frequency offset to the first signal based on a routing delay mismatch to generate the second signal such that the first transmit signal is phase coherent with the second transmit signal.

Synchronization in FMCW radar systems

According to an aspect of the present disclosure, the relative attitude between an inertial measurement unit (IMU), present on a mobile device, and the frame of reference of the vehicle carrying mobile device is estimated. The estimated relative attitude is used to translate the IMU measurement to the vehicle frame of reference to determine the velocity and position of the vehicle. As a result, the vehicle position and velocity are determined accurately in the event of undocking and re-docking of the mobile device from a docking system in the vehicle. The relative attitude is estimated in terms of pitch, roll, and yaw angles.

Undocking and re-docking mobile device inertial measurement unit from vehicle

Several systems and methods for location estimation in a multi-floor environment are disclosed. In an embodiment, the method includes performing wireless scanning so as to receive wireless signals from one or more access points from among a plurality of access points positioned at plurality of locations, respectively at one or more floors from among a plurality of floors within the multi-floor environment. A first set of RSSI measurements is computed corresponding to the wireless signals. Absolute floor location information is determined based on the first set of RSSI measurements and a pre-defined objective function. The pre-defined objective function is configured to maximize a probability of a user being located at a floor so as to receive the wireless signals. A user floor location is determined based on the absolute floor location information. The user location is estimated at least in part based on the user floor location.

Kalman filter iteratively performing time/measurement update of user/relative floor locations

In the present disclosure, an error in the velocity and position computed from a three dimensional IMU measurement is reduced confined by computing an auxiliary speed in a drive direction of a vehicle from an angular velocity measurement and a lateral acceleration measurement. The auxiliary speed is then compared with the speed computed from the acceleration measurement. The auxiliary speed is provided as the speed of the vehicle mounted with the IMU when the absolute difference between the auxiliary speed and the speed computed from the acceleration measurement in the drive direction is above a threshold. The auxiliary speed is computed when the vehicle is detected to be in a curved motion. According to another aspect of the present disclosure, the bias errors are determined when the vehicle is in a steady state, at rest or in a straight line motion. The bias errors are used to obtain the accurate auxiliary measurement.

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Bengaluru, India

Sachin Bhardwaj