A close-range microwave imaging method includes: implementing Fourier transform in a pre-set rotation axis direction on an echo signal reflected from a target object and acquired by rotating an array antenna around the pre-set rotation axis to obtain a first echo signal, wherein the first echo signal is represented in polar coordinates; multiplying the first echo signal by a pre-set reference function to obtain a second echo signal; converting the second echo signal into rectangular coordinates by a pre-set algorithm to obtain a third echo signal; and implementing three-dimensional Fourier transform on the third echo signal to obtain three-dimensional image data of the target object. By means of the method, three-dimensional image data of a target object can be obtained fast, fast imaging of the target object can be realized, the data processing amount is small, the imaging precision is high and the method is easy to implement.

A method comprising: obtaining an image; identifying a rotation angle for the image by processing the image with a first neural network; rotating the image by the identified rotation angle to generate a rotated image; classifying the image with a second neural network; and outputting an indication of an outcome of the classification, wherein the first neural network is trained, at least in part, based on a categorical distance between training data and an output that is produced by the first neural network.

The present disclosure discloses a microwave identification method, which is implemented on at least one device, including at least one processor and at least one storage device, the method including: the at least one processor obtains microwave data; the at least one processor generates an image of one or more objects based on the microwave data; the at least one processor obtains a model of each of the one or more objects; and based on the model of each of the one or more objects, the at least one processor identifies the one or more objects in the image of the one or more objects.

A system and method providing a radar-based motion-sensing user interface suitable for issuing commands to a device or system as a consequence of the detection of user motion, whole-body gestures and/or hand gestures. The system and method derive a three-dimensional representation of a user within a defined space from two-dimensional data obtained from multiple reflected radar signals. The three-dimensional representation is then processed to recognize a human body, and in particular the movement and/or position of the body and/or body parts and joints. The recognized movement and/or position are then compared to a known list of gestures and movements that are associated with particular device/system commands. If one or more of the recognized movements and/or positions conforms with a command movement/gesture, the associated command is issued to the device or system being controlled.

The present application presents various techniques for improving the performance of range tracking motion compensation method for high resolution radar imaging. Three improved techniques are described herein: improved cross-correlation alignment through updates to the reference range profile to follow the target's changing illumination angle; improved cross-correlation alignment through local peak boosting; and, improved polynomial smoothing through subdivision into multiple windows.

A millimeter-wave real-time imaging based safety inspection system and safety inspection method. The safety inspection system includes a conveying device (10), a millimeter wave transceiver module (11), an antenna array (17, 18), a switch array (16a, 16b), a switch control unit (15a, 15b), a quadrature demodulation and data acquisition module (12), and an image display unit (13). By using an Inverse Synthetic Aperture Radar (ISAR) imaging principle, the millimeter-wave real-time imaging based safety inspection system performs real-time imaging on an object to be inspected when the object moves, so that not only the imaging speed is improved, but also the field of view is enlarged. A safety inspector can determine whether an inspected person carries dangerous goods by observing a three-dimensional diagram of the inspected person, thereby eliminating the inconvenience caused by back-and-forth movement of a safety inspection device used by the safety inspector around the inspected person.

Provided is a method and system for measuring a radar cross section of an object (102). The method comprises: transmitting one or more radar pulses (402) to the object (102), each of the one or more pulses (402) having a predetermined pulse profile; for each of the one or more pulses (402), measuring a pulse return, the pulse return being the radar pulse (402) reflected by the object (102); deconvolving the measured one or more pulse returns using the predetermined pulse profile; and determining the radar cross section of the object (102) using the deconvolved one or more pulse returns.

A noise suppression method and system for Inverse Synthetic Aperture Radar micro-cluster objects using a generative adversarial network (GAN) are provided. The method includes: constructing the GAN, including a generator and a discriminator; obtaining and inputting noisy simulation data into the generator to obtain a first output, comparing the first output with noiseless simulation data to obtain a first generator loss, inputting the first output and the distribution function into the discriminator for denoising discrimination to obtain a first discriminant result, and determining a second generator loss according to the first generator loss and the first discriminate result; and obtaining measured data and inputting the measured data into the generator to obtain a second output, inputting the second output to the discriminator to obtain a second discriminant result, and determining a generator loss according to the second generator and the second discriminate result.

Antenna allocation is configured by way of a methodically random TDMA pattern that can allow the decrease in the pulse repetition rate without the reduction in the maximum resolved cross-range associated with conventional uniform TDMA. Embodiments disclosed herein offer opportunity for development of high-resolution mmWave radar systems for walk-through search and reduces the interference from surrounding objects. Other applications include synthetic-aperture radar (SAR), and other radar Range-Velocity-DOA imaging systems in automotive applications and robotics.

Systems and methods are described, and one system includes a three-dimensional (3D) geometric tracker connected to a multiband (MB) inverse synthetic aperture array radar (ISAR), and a classification/alarm logic. The MB ISAR includes spatially distributed radar transmitters (TXs) and receivers (RXs), a TX/RX allocation logic, and a tomographic (TM) image logic. The TX/RX allocation logic is configured to receive 3D tracking data from the 3D geometric tracker, indicating subject 3D position and 3D orientation and, in response, dynamically allocate TXs and RXs to maintain MB illumination of and maintain MB reception of multiple scatter angles from subjects. The TM image processor is configured to construct TM images from the scatter angles, using 3D tracking data, for input to the classification and alarm logic. Optionally, the TX/RX resource allocation logic is configured to receive situation feedback data, for feedback adjusting of allocation of TXs and RXs.