A method for determining the spatial orientation of an object from at least one measuring signal which includes the response of the object to electromagnetic interrogation radiation. A method for predicting the trajectory of at least one object from at least one measuring signal which includes the response of the object to electromagnetic interrogation radiation, in conjunction with a scalar velocity of the object. A method for training a classifier and/or a regressor.

An amplitude-phase correction method and system for a microwave imaging system are provided. The method comprises: carrying out data processing, in a range direction, on an echo signal reflected from a target object and acquired by a linear array antenna according to a first pre-set algorithm to obtain a compressed signal in the range direction; extracting a range value corresponding to the maximum amplitude, in the range direction, of the compressed signal in the range direction; carrying out time delay compensation on the echo signal according to the range value to obtain a time-delay-compensated signal; carrying out data processing on the time-delay-compensated signal according to a second pre-set algorithm to obtain an amplitude-phase signal; and carrying out amplitude-phase correction on the echo signal according to the time-delay-compensated signal and the amplitude-phase signal to obtain a corrected echo signal.

A method for determining an occupancy state of a parking space of a parking area is described. A device that includes at least one radar sensor and a processing unit, the processing unit being configured to carry out the method, are described. Furthermore, a parking area that includes at least one parking space, the parking space including the device is described.

An estimation device includes: a living body information extraction unit that extracts living body information which is a component corresponding to one or more living bodies in a space; an eigenvector calculation unit that calculates one or more eigenvectors of a living body correlation matrix obtained from the living body information; a first position estimation unit that estimates, using the living body correlation matrix, positions of the one or more living bodies and at least one false image, according to a predetermined position estimation method; a second steering vector output unit that extracts, from first steering vectors stored in a storage, and outputs as second steering vectors, first steering vectors corresponding to the positions estimated; and a second position estimation unit that estimates at least one of the position and the number of the one or more living bodies, using the one or more eigenvectors and the second steering vectors.

A wireless multimode system includes: an array of N antenna elements that includes a first portion of M antenna elements and a second portion of L antenna elements; M transmission amplifiers configured to transmit, via the M antenna elements, frames of transmit data, where the frames of transmit data include transmit radar signals and transmit communication signals; M reception amplifiers configured to receive, via the M antenna elements, frames of receive data, where the frames of receive data includes receive communication signals; and L reception amplifiers configured to receive, via the L antenna elements, receive radar signals; and a resource scheduler configured to allocate bandwidth for transmit radar signals and transmit communication signals within the frames of transmit data based on one or more predetermined parameters.

Detection of a radar target from a received radar signal includes computing a vector of filter weights dependent upon a steering vector and determining a threshold value dependent upon a designated probability of false alarm. The vector of filter weights is applied to samples of the received radar signal at a test cell, corresponding to a test range, to provide a filtered test signal and a test power of the filtered test signal is computed. The weights are also applied to samples of the received radar signal at a number of reference cells, to produce filtered reference signals. A reference power is computed from the filtered reference signals and the radar target is detected at the test range when a ratio of the test power to the reference power exceeds the threshold value.

A method for adaptively selecting a ground penetrating radar (GPR) image for detecting a moisture damage is provided. The method adaptively selects the GPR image according to a contrast of the GPR image. The method includes the following steps: S1, reading pre-processed GPR data; S2, adjusting a resolution of a picture; S3, inputting a data set into a recognition model; S4, outputting a moisture damage result; S5, judging whether there is a detection target or not by using an initial random image data set; and S6, generating the GPR image randomly incrementally and selecting the GPR image with a proper contrast. A proper B-scan image is found effectively, quickly and automatically by combining a recognition algorithm and a deep learning model or an image classification model to achieve an automatic recognition and detection based on the GPR image and improving a recognition precision as well.

A wireless multimode system includes: an array of N antenna elements that includes a first portion of M antenna elements and a second portion of L antenna elements; M transmission amplifiers configured to transmit, via the M antenna elements, frames of transmit data, where the frames of transmit data include transmit radar signals and transmit communication signals; M reception amplifiers configured to receive, via the M antenna elements, frames of receive data, where the frames of receive data includes receive communication signals; and L reception amplifiers configured to receive, via the L antenna elements, receive radar signals; and a resource scheduler configured to allocate bandwidth for transmit radar signals and transmit communication signals within the frames of transmit data based on one or more predetermined parameters.

The method includes a step of forming, with a radar, a number N of beams of equal angular width that irradiate a runway and a portion of the surroundings of the runway; a step of dividing the zone irradiated by the beams into distance-angle boxes, the beams delineating the boxes anglewise; a step of taking measurements of backscattered power received from distance-angle boxes, the measurements being carried out for a set of pairs of boxes, a pair being composed of two boxes of same distance one of which, called the right box, crosses the right edge (3D) of the runway, and the other of which, called the left box, crosses the left edge (3G); a step of computing, for each pair, the difference in backscattered power between the right box and the left box, the aircraft being aligned with the axis when the difference is zero for at least two pairs of distance-angle boxes.

The present application discloses a new form of μ-STAP, referred to herein as post μ-STAP or Pμ-STAP, which overcomes the drawbacks associated with existing μ-STAP techniques. The Pμ-STAP techniques described herein facilitate the generation of additional training data and homogenization after pulse compression. For example, Pμ-STAP techniques may apply a plurality of homogenization filters to a pulse compressed datacube generated from an input radar waveform, which produces a plurality of new pulse compressed datacubes with improved characteristics. Unlike existing μ-STAP techniques described above, which require prepulse compressed data to operate, the Pμ-STAP techniques disclosed in the present application are designed to utilize pulse compressed data, and therefore may be readily applied to legacy radar systems.