A localization method for locating a target that is coupled with a locator transponder associated with a permanent identification code permanently assigned to the locator transponder is provided. The localization method includes: a) transmitting a spread spectrum paging signal carrying the permanent identification code and a shorter temporary identification code temporarily assigned to the locator transponder; b) receiving the spread spectrum paging signal and extracting the temporary identification code carried by the received spread spectrum paging signal; c) transmitting radar signals towards area(s) of earth's surface or sky and receiving echo signals therefrom; d) upon reception by the locator transponder of radar signal(s), generating and transmitting a sequence of watermarked radar echo signals in which a spread spectrum watermarking signal is embedded that includes the temporary identification code; e) carrying out localization operations; f) transmitting frequency-synchronization-aid signal(s); g) receiving the frequency-synchronization-aid signal(s) and estimating a frequency drift affecting a reference frequency provided by a local oscillator of the locator transponder; wherein the locator transponder transmits the sequence of watermarked radar echo signals by using a transmission carrier frequency obtained based on the reference frequency provided by the local oscillator and on the estimated frequency drift.

A constellation of satellites and associated methods for Earth Observation are disclosed. One method includes transmitting a set of at least four signals towards the Earth using a constellation of at least four satellites and receiving a set of at least four reflected signals from the Earth using the constellation. The method also includes analyzing, using a set of at least four signal analyzers, the set of at least four signals to generate a set of data. Each satellite in the constellation individually houses a signal analyzer in the set of at least four signal analyzers. The method also includes deriving the set of Earth observations using the set of data. Each satellite receives a signal in the set of at least four signals from every other satellite in the constellation.

A method includes transmitting, by a radiofrequency identification (RFID) reader device, a first electromagnetic radiation at a first polarization to a scan area and second electromagnetic radiation at a second polarization to the scan area. Re-radiated first electromagnetic radiation is received from an RFID tag located in the scan area at the first polarization. Re-radiated second electromagnetic radiation is received from the RFID tag at the second polarization. A radar image is generated based on the first and second re-radiated electromagnetic radiation. One or more items of information encoded in one or more microstructure elements located on the RFID tag are decoded based on the generated radar image. An RFID reader device and an RFID system are also disclosed.

A process and systems for constructing arbitrarily large virtual arrays using two or more collection platforms (e.g. AUX and MOV systems) having differing velocity vectors. Referred to as Motion Extended Array Synthesis (MXAS), the resultant imaging system is comprised of the collection of baselines that are created between the two collection systems as a function of time. Because of the unequal velocity vectors, the process yields a continuum of baselines over some range, which constitutes an offset imaging system (OIS) in that the baselines engendered are similar to those for a real aperture of the same size as that swept out by the relative motion, but which are offset by some (potentially very large) distance.

A data generation device is provided with environment setting means (200), model setting means (210), image calculation means (220) and data output means (230). The environment setting means sets a radar parameter that indicates a specification of a radar that is a synthetic aperture radar or an inverse synthetic aperture radar. The model setting means sets a three-dimensional model that indicates a shape of a target object to identify. The image calculation means calculates a simulation image based on the three-dimensional model and the radar parameter. The data output means outputs training data in that the simulation image and a type of the target object are associated to each other. In addition, the data output means outputs difference data that indicate a difference between a radar image and the simulation image. The model setting means changes the three-dimensional model based on model correction data inputted based on the difference data.

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.

A controller is configured to be coupled to a millimeter-wave radar mounted on a device, where the millimeter-wave radar includes a field of view in a direction away from the device. The controller is configured to: detect a presence of an object in a first range zone of a plurality of range zones of the field of view, where each range zone of the plurality of range zones respectively corresponds to different distance ranges relative to the device, and where each range zone is associated with a respective command database; determine a gesture signature based on detecting the presence of the object in the first range zone of the field of view; and cause execution of a command chosen from the respective command database associated with the first range zone as a function of the gesture signature.

A method for measuring a Radar Cross Section, RCS, of an object (200), wherein the method comprises: acquiring (S1000), by a first antenna (100), observations of the object (200) by performing two dimensional near field frequency scans; computing (S1100), by a processor, the downrange profiles of the acquired observations; computing (S1200), by the processor, the three dimensional Inverse Synthetic Aperture Radar, ISAR, images by superimposing the downrange profiles; extracting (S1300), by the processor, the scattering center of the object (200); and computing (S1400), by the processor, the RCS of the object (200).

Multistatic radar systems and associated methods are disclosed herein. In some embodiments, a multistatic radar system can include multiple radar transmitters and multiple radar receivers. The transmitters are configured to generate radio-frequency (RF) signals in a target volume, and the receivers are configured to receive the RF signals after the RF signals are reflected off an object moving through the target volume. The transmitters and the receivers can be spaced apart and aperiodically positioned about the target volume. The receivers can sample and digitize the reflected RF signals at an RF frequency. The radar system further includes a processing device configured to determine a property of the object based on the sampled reflected RF signals.

An imaging system to reconstruct a reflectivity image of a scene including an object moving with the scene. A tracking system to track a deforming object to estimate an object deformation for each time step. Sensors acquire snapshots of the scene, each acquired snapshot of the object includes measurements in the object deformation for that time step, to produce a set of object measurements with deformed shapes over the time steps. Compute a correction to estimates of object deformation for each time step, with matching measurements of the corrected object deformation for each time step to measurements in the acquired snapshot of object for that time step. Select a corrected deformation over other corrected deformations for each time step, according to a distance between the corrected deformation and the estimate of the deformation, to obtain a final estimate of the deformation of the deformable object moving in the scene.