A multichannel radar system comprising a set of antennas each receiving a sequence of chirps reflected from plurality of objects, a range detector generating a set of range bins for each chirp, a beam former operative to generate a set of dominant frequency components from a group of range bins picked from the set of range bins across the set of antennas, a nearness detector for separating the set of dominant frequencies into a first set of dominant frequencies and a second set of dominant frequencies, a frequency subtractor configured to shift the each dominant frequency in the first set of dominant frequencies by its phase by a first value to form a third set of phase shifted dominant frequencies, and a Doppler estimator estimating a Doppler frequency of the each dominant frequency in the set of dominant frequencies from the third set of phase shifted dominant frequencies and the second set of dominant frequencies.

A radio detection and ranging (radar) operating apparatus includes: radar sensors configured to receive signals reflected from an object; and a processor configured to generate Doppler maps for the radar sensors based on the reflected signals and estimate a time difference between the radar sensors based on the generated Doppler maps.

A radar processor for processing a frame of radar data received from one or more targets, the frame of radar data having a carrier frequency and comprising a sequence of codewords with a codeword repetition interval, wherein the carrier frequency and the codeword repetition interval define an unambiguous velocity range, the radar processor configured to: receive the frame of radar data; transform the frame to obtain a velocity data array; apply a correction algorithm to the velocity data array to correct a Doppler shift of the frame to obtain a corrected array, wherein the correction algorithm comprises a set of Doppler correction frequencies corresponding to a set of velocity gates and at least one of the set of Doppler correction frequencies corresponds to a velocity gate outside the unambiguous velocity range; and perform range processing on the corrected array to obtain a range-Doppler map.

A radar processor for processing a frame of radar data received from one or more targets, the frame of radar data having a carrier frequency and comprising a sequence of codewords with a codeword repetition interval, wherein the carrier frequency and the codeword repetition interval define an unambiguous velocity range, the radar processor configured to: receive the frame of radar data; transform the frame to obtain a velocity data array; apply a correction algorithm to the velocity data array to correct a Doppler shift of the frame to obtain a corrected array, wherein the correction algorithm comprises a set of Doppler correction frequencies corresponding to a set of velocity gates and at least one of the set of Doppler correction frequencies corresponds to a velocity gate outside the unambiguous velocity range; and perform range processing on the corrected array to obtain a range-Doppler map.

A signal processing unit and a method for searching for peaks in a two-dimensional matrix of numbers are described. The matrix is analyzed row by row and then column by column. Analyzing a row comprises, for each element of the row, tagging the element in response to determining that the element is a local maximum of the row Analyzing a column comprises determining a bit field associated with the column by determining, for each element of the column, a corresponding bit field element Determining the bit field element comprises: if the element of the column has not been tagged, setting the bit field element to a predefined first value, and, if the element of the column has been tagged, determining whether the element is a local maximum and, in this case, setting the bit field element to a predefined second value different from the first value and, otherwise, setting the bit field element to the first value.

A signal processing unit and a method for searching for peaks in a two-dimensional matrix of numbers are described. The matrix is analyzed row by row and then column by column. Analyzing a row comprises, for each element of the row, tagging the element in response to determining that the element is a local maximum of the row Analyzing a column comprises determining a bit field associated with the column by determining, for each element of the column, a corresponding bit field element Determining the bit field element comprises: if the element of the column has not been tagged, setting the bit field element to a predefined first value, and, if the element of the column has been tagged, determining whether the element is a local maximum and, in this case, setting the bit field element to a predefined second value different from the first value and, otherwise, setting the bit field element to the first value.

Some embodiments are directed to methods of detecting a target that include: receiving signals reflected from a target of interest, the signals having a bandwidth large enough to provide a plurality of range cells along an expected target, and processing the received signal(s) by (i) determining the phases of contiguous groups of range cells, the group size selected to approximate to sizes of targets of interest, (ii) phase-shifting the returns within a group to increase constructive interference and thereby signal power; and (iii) combining the phase shifted returns to produce phase-adjusted combined returns, and performing a detection on those combined returns. Some embodiments may provide enhanced target detection capabilities. The process may be repeated for different potential target sizes, and may be performed either on real time data, or off-line on recorded data, and is applicable to both radar and sonar.

Some embodiments are directed to methods of detecting a target that include: receiving signals reflected from a target of interest, the signals having a bandwidth large enough to provide a plurality of range cells along an expected target, and processing the received signal(s) by (i) determining the phases of contiguous groups of range cells, the group size selected to approximate to sizes of targets of interest, (ii) phase-shifting the returns within a group to increase constructive interference and thereby signal power; and (iii) combining the phase shifted returns to produce phase-adjusted combined returns, and performing a detection on those combined returns. Some embodiments may provide enhanced target detection capabilities. The process may be repeated for different potential target sizes, and may be performed either on real time data, or off-line on recorded data, and is applicable to both radar and sonar.

This disclosure relates generally to material quality inspection. Conventional approaches available for material quality inspection are unable to address concerns of complexity and cost involved. The technical problem of occluded object detection and material quality inspection for intrinsic defects identification is addressed in the present disclosure. The present disclosure provides a system and method for non-intrusive material quality inspection using three-dimensional monostatic radar based imaging, where the object under inspection undergoes a circular translation motion on a rotating platform. A modified delay-and-sum (m-DAS) algorithm is built by incorporating virtual antenna array to obtain a 3D image reconstruction of the object. From 3D reconstructed images, radial displacement as well as the angular locations of the object is identified which are further used for quality inspection of the material comprised in the object.

This disclosure relates generally to material quality inspection. Conventional approaches available for material quality inspection are unable to address concerns of complexity and cost involved. The technical problem of occluded object detection and material quality inspection for intrinsic defects identification is addressed in the present disclosure. The present disclosure provides a system and method for non-intrusive material quality inspection using three-dimensional monostatic radar based imaging, where the object under inspection undergoes a circular translation motion on a rotating platform. A modified delay-and-sum (m-DAS) algorithm is built by incorporating virtual antenna array to obtain a 3D image reconstruction of the object. From 3D reconstructed images, radial displacement as well as the angular locations of the object is identified which are further used for quality inspection of the material comprised in the object.