Abstract: The present disclosure provides a method for surface wear inspection using millimeter wave radar. The system initially receives a plurality of uncompressed raw Synthetic Aperture Radar (SAR) images. Further, a plurality of reconstructed SAR images are generated based on the plurality of uncompressed raw SAR images using a variable focusing based Range Doppler Algorithm (RDA). Further, a master image and a slave image are selected from the reconstructed SAR images and corresponding anchor points are assigned. Further a plurality of fine level and coarse level shift coordinates are computed based on the corresponding anchor points. Further, a net shift value is computed based on the plurality of fine level and coarse level shift coordinates. The master and the slave images are aligned based on the net shift value and the interferogram is generated. The interferogram is further analyzed to profile the corresponding deformation pertaining to the surface under test.

Abstract: This disclosure relates to systems and methods for shapelet decomposition based recognition using radar. State-of-the-art solutions involve use of standard machine learning classification techniques for gesture recognition which suffer with problem of dependency on collected data. The present disclosure overcome the limitations faced by the state-of-the-art solutions by obtaining a plurality of time domain signal using a radar system comprising three vertically arranged radars and one or more sensors, identifying one or more gesture windows to obtain one or more shapelets corresponding to one or gestures which are further decomposed into a plurality of sub shapelets. Further, at least one of (i) a positive or (i) a negative time delay is applied to each of the plurality of sub shapelets to obtain a plurality of composite shapelets which are further mapped with a plurality of trained shapelets to recognize gestures comprised in one or more activities performed by a subject.

Abstract: 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.

Abstract: This disclosure relates to selection of optimum channel in twin radars for efficient detection of cardiopulmonary signal rates. State-of-the-art solutions involve use of IQ (In-phase and Quadrature) channel radar which need continuous calibration. Distance of the radar from a subject being monitored affects performance. The present disclosure enables enhanced cardiopulmonary signal rate monitoring using a time domain approach, wherein only the data from signal reflected off the radar is considered. The solution is also time window adaptive. Signal property and radar physics-based methods have been implemented for selecting an optimum channel in twin radars thereby enhancing detection of respiration rate and breath rate.

Abstract: Lighting conditions affect quality of images being captured. In traditional systems, illuminators (light sources) are used to illuminate the objects without considering illumination levels at different zones/sides of an object being photographed. As a result, all illuminators may run at maximum capacity, resulting in wastage of power and compromising efficiency of the system. The disclosure herein generally relates to illumination of objects, and, more particularly, to a method and system for adaptive illumination of objects. The system determines illumination at different zones of the object, and further identifies zones that are not illuminated properly in comparison with a threshold of illumination.

Abstract: The disclosure herein generally relates to the field of determination of cardiopulmonary signals for multi-persons, and, more particularly, to determination of cardiopulmonary signals for multi-persons using in-body signals obtained by ultra-wide band (UWB) radar. The disclosed method determines of cardiopulmonary signals for multi-persons using in-body signals, wherein a UWB radar signals/waves reflected from inside a human body is utilized for efficient determination of cardiopulmonary signals. The disclosed method and system utilize the UWB radar signals to identify a number of persons along with several details about the persons that include a girth of the each identified person and the orientation of the identified person towards the one or more UWB radar. Further a chest wall distance, a breathing rate, a heart wall distance and a heart rate are determined for all the identified persons based on the identified girth and the identified orientation along with the UWB radar signals.

Abstract: Radar based HR and BR measurements by simultaneous decoding is a technical problem due to presence of intermodulation of BR and HR harmonics, which degrades simultaneous decoding. Embodiments herein provide a method and system for unobtrusive liveliness detection and monitoring of a subject using a Dual Frequency Radar (DFR) in an IOT network. The system has the capability to completely process the captured raw signals onboard to by applying required signal conditioning and extraction of relevant information using unique signal processing techniques for determining the HR and the BR of the subject accurately. The intermodulation of BR and HR harmonics is eliminated by the system by performing frequency spectrum averaging of both radars signals, which improves the accuracy. Further, the system is configured with a light MQTT protocol and encoding modules for any data to be shared for off board processing, ensuring data security and privacy compliance.

Abstract: An e-commerce business model has witnessed several cases where packages with faulty goods, returned by buyers, without procured object, rather replaced by different device. This disclosure relates a method to detect whether object under test a desired object. A plurality of back-scattered signals is received from the object under test occluded by packaging with continuous motion on conveyer based on first antenna-radar combination. The plurality of back-scattered signals is processed by applying four-tap difference filter to obtain motion-filtered data matrix. A low pass filter is applied on the motion-filtered data matrix to obtain enveloped motion-filtered data matrix. A sliding constant false alarm rate is applied on the enveloped motion-filtered data matrix to determine detection threshold value. A check is performed to detect whether the object under test is the desired object based on whether intensity of the plurality back-scattered signals exceeds the detection threshold value.

Abstract: This disclosure relates generally to methods and systems for real time unobtrusive monitoring of physiological signals of a subject confined to a bed. Output of single channel continuous wave (CW) radars are dependent upon distance of the subject from the radar. Dual channel IQ radars are more accurate but are costly and availability in the market is a constraint. The present disclosure provides a cheap and easily replicable pseudo IQ radar based system. The pseudo IQ radar comprises two CW radars placed at a calibrated distance from each other such that optimum points of one CW radar spatially overlaps null points of the other CW radar and phase imbalance is suppressed. Three such pseudo IQ radars are positioned in a predetermined configuration around the subject being monitored. A Supervised Complex Signal Demodulation (SCSD) method configured to suppress amplitude and DC imbalance is also provided for evaluating the physiological signals.

Abstract: The disclosure herein generally relates to the field of determination of cardiopulmonary signals for multi-persons, and, more particularly, to determination of cardiopulmonary signals for multi-persons using in-body signals obtained by ultra-wide band (UWB) radar. The disclosed method determines of cardiopulmonary signals for multi-persons using in-body signals, wherein a UWB radar signals/waves reflected from inside a human body is utilized for efficient determination of cardiopulmonary signals. The disclosed method and system utilize the UWB radar signals to identify a number of persons along with several details about the persons that include a girth of the each identified person and the orientation of the identified person towards the one or more UWB radar. Further a chest wall distance, a breathing rate, a heart wall distance and a heart rate are determined for all the identified persons based on the identified girth and the identified orientation along with the UWB radar signals.

Abstract: This disclosure relates generally to action recognition and more particularly to system and method for real-time radar-based action recognition. The classical machine learning techniques used for learning and inferring human actions from radar images are compute intensive, and require volumes of training data, making them unsuitable for deployment on network edge. The disclosed system utilizes neuromorphic computing and Spiking Neural Networks (SNN) to learn human actions from radar data captured by radar sensor(s). In an embodiment, the disclosed system includes a SNN model having a data pre-processing layer, Convolutional SNN layers and a Classifier layer. The preprocessing layer receives radar data including doppler frequencies reflected from the target and determines a binarized matrix. The CSNN layers extracts features (spatial and temporal) associated with the target's actions based on the binarized matrix.

Abstract: The disclosure generally relates to determining a breathing rate and a heart rate from cardiopulmonary signal. Conventional systems use additional hardware to improve signal quality or different signal processing techniques to calculate the heart rate from the cardiopulmonary signal. However accurately determining the heart rate is always a continuous area of an improvement. The present methods and systems solve the problem of determining the heart rate accurately, from the cardiopulmonary signals, by determining the signal quality of the cardiopulmonary signal and the signal associated with the heart rate, comprised in the cardiopulmonary signal. A signal processing technique that best performs, out of a set of signal processing techniques is identified based on the signal quality to determine the heart rate. A long-term and an effective health monitoring of healthy as well as patient and infant subjects is achieved by the present disclosure.

Abstract: Radar based HR and BR measurements by simultaneous decoding is a technical problem due to presence of intermodulation of BR and HR harmonics, which degrades simultaneous decoding. Embodiments herein provide a method and system for unobtrusive liveliness detection and monitoring of a subject using a Dual Frequency Radar (DFR) in an IOT network. The system has the capability to completely process the captured raw signals onboard to by applying required signal conditioning and extraction of relevant information using unique signal processing techniques for determining the HR and the BR of the subject accurately. The intermodulation of BR and HR harmonics is eliminated by the system by performing frequency spectrum averaging of both radars signals, which improves the accuracy. Further, the system is configured with a light MQTT protocol and encoding modules for any data to be shared for off board processing, ensuring data security and privacy compliance.

Abstract: This disclosure relates to systems and methods for shapelet decomposition based recognition using radar. State-of-the-art solutions involve use of standard machine learning classification techniques for gesture recognition which suffer with problem of dependency on collected data. The present disclosure overcome the limitations faced by the state-of-the-art solutions by obtaining a plurality of time domain signal using a radar system comprising three vertically arranged radars and one or more sensors, identifying one or more gesture windows to obtain one or more shapelets corresponding to one or gestures which are further decomposed into a plurality of sub shapelets. Further, at least one of (i) a positive or (i) a negative time delay is applied to each of the plurality of sub shapelets to obtain a plurality of composite shapelets which are further mapped with a plurality of trained shapelets to recognize gestures comprised in one or more activities performed by a subject.

Abstract: This disclosure relates generally to radar based human activity detection, and, more particularly to, systems and methods from radar based human activity detection and three-dimensional (3D) reconstruction of human gestures using configurable panel radar system. Traditional systems and methods may not provide for a separate capturing of top and bottom parts of the human body. Embodiment of the present disclosure overcome the limitations faced by the traditional systems and methods by identifying a user that performed a gesture; detecting each gesture performed by the identified user; generating, by simulating a set of gesture labels, a sensor data and the generated metadata, a two-dimensional (2D) reference database of different speeds of the detected gestures; computing a displacement and a time of the detected gestures via a pattern matching technique; and reconstructing a video of the identified user performing the detected gestures in 3D.

Abstract: This disclosure relates to selection of optimum channel in twin radars for efficient detection of cardiopulmonary signal rates. State-of-the-art solutions involve use of IQ (In-phase and Quadrature) channel radar which need continuous calibration. Distance of the radar from a subject being monitored affects performance. The present disclosure enables enhanced cardiopulmonary signal rate monitoring using a time domain approach, wherein only the data from signal reflected off the radar is considered. The solution is also time window adaptive. Signal property and radar physics-based methods have been implemented for selecting an optimum channel in twin radars thereby enhancing detection of respiration rate and breath rate.

Abstract: This disclosure relates to non-contact inspection of material for identifying and estimate composition of a material under inspection. Traditionally, material inspection is an invasive process involving contact based approaches. A radar-based approach requires placement of the radar at a specific location, which is a challenge since amplitude of the reflected signal, depends on the distance from the material under inspection. The present disclosure addresses this technical problem by providing a Continuous Wave radar-based approach that is based on absolute slope at extrema points on the reflected signal from the material under inspection.

Abstract: This disclosure relates generally to radar based human activity detection, and, more particularly to, systems and methods from radar based human activity detection and three-dimensional (3D) reconstruction of human gestures using configurable panel radar system. Traditional systems and methods may not provide for a separate capturing of top and bottom parts of the human body. Embodiment of the present disclosure overcome the limitations faced by the traditional systems and methods by identifying a user that performed a gesture; detecting each gesture performed by the identified user; generating, by simulating a set of gesture labels, a sensor data and the generated metadata, a two-dimensional (2D) reference database of different speeds of the detected gestures; computing a displacement and a time of the detected gestures via a pattern matching technique; and reconstructing a video of the identified user performing the detected gestures in 3D.

Abstract: This disclosure relates to non-contact inspection of material for identifying and estimate composition of a material under inspection. Traditionally, material inspection is an invasive process involving contact based approaches. A radar-based approach requires placement of the radar at a specific location, which is a challenge since amplitude of the reflected signal, depends on the distance from the material under inspection. The present disclosure addresses this technical problem by providing a Continuous Wave radar-based approach that is based on absolute slope at extrema points on the reflected signal from the material under inspection.

Abstract: This disclosure relates generally to methods and systems for real time unobtrusive monitoring of physiological signals of a subject confined to a bed. Output of single channel continuous wave (CW) radars are dependent upon distance of the subject from the radar. Dual channel IQ radars are more accurate but are costly and availability in the market is a constraint. The present disclosure provides a cheap and easily replicable pseudo IQ radar based system. The pseudo IQ radar comprises two CW radars placed at a calibrated distance from each other such that optimum points of one CW radar spatially overlaps null points of the other CW radar and phase imbalance is suppressed. Three such pseudo IQ radars are positioned in a predetermined configuration around the subject being monitored. A Supervised Complex Signal Demodulation (SCSD) method configured to suppress amplitude and DC imbalance is also provided for evaluating the physiological signals.