Texas Instruments Corporation

Dan Wang

Adeel Ahmad

Murtaza Ali

Sandeep Rao

Muhammad Zubair Ikram

Karthik Subburaj

Arthur John Redfern

Brian Paul Ginsburg

June Chul Roh

Lorin Paul Netsch

Meysam Moallem

Gregory Jan Malysa

Vikram Vijayanbabu Appia

Anil Varghese Mani

In an example, a method is implemented in a radar system. The method may include transmitting, via transmission channels, a frame of chirps, the chirps transmitted having a programmed frequency offset that is a function of a transmission channel of the transmission channels that is transmitting the frame of chirps, receiving, via a receive channel, a frame of reflected chirps, the reflected chirps comprising the chirps reflected by an object within a field of view of the radar system, and determining a Doppler domain representation of the frame of reflected chirps having a Doppler domain spectrum that includes multiple spectrum bands, the object represented in at least a portion of the spectrum bands based on the reflected chirps, wherein the programmed frequency is configured to cause the Doppler domain spectrum to include a number of spectrum bands greater than the number of transmission channels.

Empty band doppler division multiple access

A matrix compression/decompression accelerator (MCA) system/method that coordinates lossless data compression (LDC) and lossless data decompression (LDD) transfers between an external data memory (EDM) and a local data memory (LDM) is disclosed. The system implements LDC using a 2D-to-1D transformation of 2D uncompressed data blocks (2DU) within LDM to generate 1D uncompressed data blocks (1DU). The 1DU is then compressed to generate a 1D compressed superblock (CSB) in LDM. This LDM CSB may then be written to EDM with a reduced number of EDM bus cycles. The system implements LDD using decompression of CSB data retrieved from EDM to generate a 1D decompressed data block (1DD) in LDM. A 1D-to-2D transformation is then applied to the LDM 1DD to generate a 2D decompressed data block (2DD) in LDM. This 2DD may then be operated on by a matrix compute engine (MCE) using a variety of function operators.

Matrix compression accelerator system and method

In accordance with described examples, a method determines if a velocity of an object detected by a radar is greater than a maximum velocity by receiving on a plurality of receivers at least one frame of chirps transmitted by at least two transmitters and reflected off of the object. A velocity induced phase shift (φ) in a virtual array vector S of signals received by each receiver corresponding to a sequence of chirps (frame) transmitted by each transmitter is estimated. Phases of each element of virtual array vector S are corrected using φto generate a corrected virtual array vector S. A first Fourier transform is performed on the corrected virtual array vector Sto generate a corrected virtual array spectrum to detect a signature that indicates that the object has an absolute velocity greater than a maximum velocity.

Methods and apparatus for velocity detection in MIMO radar including velocity ambiguity resolution

An apparatus, including processing unit (PU) cores and computer readable storage devices storing machine instructions for determining a distance between a target object and a radar sensor circuit. The PU cores receive a beat signal generated by the radar sensor circuit and compensate for a phase difference between the received beat signal and a reconstruction of the received beat signal to obtain a phase compensated beat signal. The phase compensated beat signal is then filtered to remove spurious reflections by demodulating the phase compensated beat signal using an estimated frequency of the phase compensated beat signal. The PU cores then apply a low pass filter to the demodulated phase compensated beat signal, resulting in a modified beat signal. The PU cores then determine the distance between the target object and the radar sensor circuit using the modified beat signal.

Distance measurement using millimeter wave radar

A radar system comprises a set of transmitters and a processor coupled to the set of transmitters. The processor is configured to modulate a first portion of a chirp in a chirp frame according to a first phase. The processor is further configured to modulate a second portion of the chirp in the chirp frame according to a second phase and configured to combine the first and second portions of the chirp to produce a phase-modified chirp. The processor is further configured to instruct the set of transmitters to transmit the phase-modified chirp by applying time division multiple access (TDMA) and by directing radio frequency energy according to a target angle and a target gain.

Simultaneous beamforming and multiple input-multiple output (MIMO) schemes in radar system

A mm-wave system includes transmission of a millimeter wave (mm-wave) signal by a plurality of transmitters to multiple objects, and receiving of return—mm-wave signals from the multiple objects by a plurality of receivers. A processor is configured to perform an algorithm to derive complex-valued samples and angle measurements from each receiver to identify one object from another object. The processor further extracts signal waveforms that correspond to each object and process the extracted signal waveforms to estimate breathing rate and heart rate of the identified object.

Multi-person vital signs monitoring using millimeter wave (mm-wave) signals

A millimeter or mm-wave system includes transmission of a millimeter wave (mm-wave) radar signal by a transmitter to an object. The transmitted mm-wave radar signal may include at least two signal orientations, and in response to each signal orientation, the object reflects corresponding signal reflections. The signal reflections are detected and a determination is made as to location of the object.

Slim object detection using multi-polarized radar signals

A mm-wave system includes transmission of a millimeter wave (mm-wave) signal by a plurality of transmitters to multiple objects, and receiving of return-mm-wave signals from the multiple objects by a plurality of receivers. A processor is configured to perform an algorithm to derive complex-valued samples and angle measurements from each receiver to identify one object from another object. The processor further extracts signal waveforms that correspond to each object and process the extracted signal waveforms to estimate breathing rate and heart rate of the identified object.

In accordance with described examples, a method determines if a velocity of an object detected by a radar is greater than a maximum velocity by receiving on a plurality of receivers at least one frame of chirps transmitted by at least two transmitters and reflected off of the object. A velocity induced phase shift (&#x3c6;) in a virtual array vector S of signals received by each receiver corresponding to a sequence of chirps (frame) transmitted by each transmitter is estimated. Phases of each element of virtual array vector S are corrected using &#x3c6;to generate a corrected virtual array vector S. A first Fourier transform is performed on the corrected virtual array vector Sto generate a corrected virtual array spectrum to detect a signature that indicates that the object has an absolute velocity greater than a maximum velocity.

In the proposed low complexity technique a hierarchical approach is created. An initial FFT based detection and range estimation gives a coarse range estimate of a group of objects within the Rayleigh limit or with varying sizes resulting from widely varying reflection strengths. For each group of detected peaks, demodulate the input to near DC, filter out other peaks (or other object groups) and decimate the signal to reduce the data size. Then perform super-resolution methods on this limited data size. The resulting distance estimations provide distance relative to the coarse estimation from the FFT processing.

Low complexity super-resolution technique for object detection in frequency modulation continuous wave radar

A system includes a frequency modulated continuous wave (FMCW) transceiver, a processor, and a memory. The memory stores program instructions that, when executed by the processor, cause the system to receive a signal representative of an FMCW signal reflected from an object of interest, apply a first Fourier transform to the signal to obtain range data, identify a subset of the range data corresponding to a region of interest, apply a second Fourier transform on the identified subset of the range data to obtain velocity data corresponding to the identified subset of the range data, and identify a gesture performed by the object of interest based on at least a portion of velocity data.

Hidden markov model-based gesture recognition with FMCW radar

A method of generating an alignment matrix for a camera-radar system includes: receiving radar data originated by a radar subsystem and representative of an area of interest within a field of view for the radar subsystem; receiving image data originated by a camera subsystem and representative of the area of interest within a field of view for the camera subsystem; processing the radar data to detect features within the area of interest and to determine a reflected radar point with three dimensions relating to a camera-radar system; processing the image data to detect features within the area of interest and to determine a centroid with two dimensions relating to the camera-radar system; and computing an alignment matrix for radar and image data from the camera-radar system based on a functional relationship between the three dimensions for the reflected radar point and the two dimensions for the centroid.

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Allen, TX, United States of America

Dan Wang