A system for virtual aperture array radar tracking includes a transmitter that transmits first and second probe signals; a receiver array including a first plurality of radar elements positioned along a first radar axis; and a signal processor that calculates a target range from first and second reflected probe signals, corresponds signal instances of the first reflected probe signal to physical receiver elements of the radar array, corresponds signal instances of the second reflected probe signal to virtual elements of the radar array, calculates a first target angle between a first reference vector and a first projected target vector from the first reflected probe signal, and calculates a position of the tracking target relative to the radar array from the target range and first target angle.

A system for virtual aperture array radar tracking includes a transmitter that transmits first and second probe signals; a receiver array including a first plurality of radar elements positioned along a first radar axis; and a signal processor that calculates a target range from first and second reflected probe signals, corresponds signal instances of the first reflected probe signal to physical receiver elements of the radar array, corresponds signal instances of the second reflected probe signal to virtual elements of the radar array, calculates a first target angle between a first reference vector and a first projected target vector from the first reflected probe signal, and calculates a position of the tracking target relative to the radar array from the target range and first target angle.

A computing machine receives a real synthetic aperture radar (SAR) image including one or more targets. The real SAR image is one of a plurality of real SAR images in a training set. The computing machine generates, for the real SAR image, a model-based target shadow background (TSB) image using a three-dimensional (3D) model of the target. The computing machine generates, for the real SAR image and using an auto-encoder engine, an auto-encoder-generated TSB image using an artificial neural network (ANN). The computing machine computes, using a discriminator engine, an image difference between the auto-encoder-generated TSB image and the model-based TSB image. The computing machine adjusts weights in the auto-encoder engine based on the computed image difference.

A method for training a trainable module for evaluating radar signals. The method includes feeding actual radar signals and/or actual representations derived therefrom of a scene observed using the actual radar signals to the trainable module and conversion thereof by this trainable module to processed radar signals and/or to processed representations of the respective scene, and using a cost function to assess to what extent the processed radar signals are suited for reconstructing a movement of objects or to what extent the processed representations contain artifacts of moving objects in the scene. Parameters, which characterize the performance characteristics of a trainable module, are optimized with regard to the cost function. A method is also provided for evaluating moving objects from radar signals.

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.

The present invention relates to the technical fields of optical imaging, microwave imaging, radar detection, sonar, ultrasonic imaging, and target detection, imaging identification and wireless communication based on media such as sound, light and electricity, and in particular, to a fast imaging method suitable for passive imaging and active imaging and application of the fast imaging method in the above fields. According to the method provided by the present invention, image field distribution corresponding to a target is achieved based on a lens imaging principle, in combination with an electromagnetic field theory, according to a target signal received by an antenna array, through the amplitude and phase weighting of a unit signal and by using an efficient parallel algorithm. The method provided by the present invention has the advantages of capability of being compatible with passive imaging and holographic imaging, good imaging effect, small operation amount, low hardware cost, high imaging speed and suitability for long-distance imaging, and can be widely applied in the fields of optical imaging, microwave imaging, radar detection, sonar, ultrasonic imaging, and target detection, imaging identification and wireless communication based on media such as sound, light and electricity.

A self-contained, high precision navigation method and system for a mobile vehicle comprising an active coherent imaging sensor array with multiple receivers that observes the surrounding environment and a digital processing component that processes the received signals to form interferometric images and determine the precise three-dimensional location and three-dimensional orientation of the vehicle within that environment.

An image analysis device that ease association between an SAR image and an object is provided. The image analysis device includes: a stable reflection point identification unit that identifies, based on a plurality of synthetic aperture radar (SAR) images, stable reflection points at which reflection is stable in the plurality of SAR images; a phase identification unit that identifies a phase at each of the stable reflection points, based on the plurality of SAR images and a location of the stable reflection point in the plurality of SAR images; and a clustering means that clusters the stable reflection points, based on a Euclidian distance between each of the stable reflection points and a correlation of the phases at each of the stable reflection points.

A method for calculating a sensitivity of a displacement of Synthetic Aperture Radar (SAR) along line-of-sight direction to a slope gradient and a slope aspect is provided, comprising: obtaining SAR data and Digital Elevation Model (DEM) data covering slope bodies, and extracting a local incident angle of an image by utilizing a satellite side-looking imaging principle; carrying out geometric distortion on the slope bodies under ascending and descending orbits by utilizing the local incident angle, to obtain specific locations of geometric distortion areas under ascending and descending orbit; calculating sensitivities of detections to changes of the slope gradient and the slope aspect under ascending and descending orbits according to the extracted parameter information of the SAR satellite in ascending and descending orbits and satellite heights, and dividing a sensitivity distribution by combining the sensitivity and the specific locations of the geometric distortion.

A navigation apparatus includes an image capturing device, template database, correlation device, evaluation device, and output interface. The image capturing device can create a radar image of a surround, the template database configured to provide at least one template substantially matched to the radar image and containing at least one geo-referenced landmark, the at least one geo-referenced landmark being geo-referenced by at least one geo-coordinate. The correlation device can correlate the at least one geo-referenced landmark in the at least one template with the radar image and provide the at least one geo-coordinate belonging to the at least one geo-referenced landmark. The evaluation device can determine a position of the navigation apparatus from the at least one geo-coordinate of the at least one geo-referenced landmark and from a setting of the image capturing device. The output interface is configured to provide the determined position.