Abstract:
A method of target feature extraction and multi-target tracking based on 4D millimeter wave radar includes acquiring the point cloud data output from the radar and preprocess the point cloud data to eliminate the outlier value; processing the points acquired after preprocessing by Density-Based Spatial Clustering of Applications with Noise (DBSCAN) clustering; processing each of the acquired clusters for target feature extraction; predicting the existing trajectory is predicted, and the prediction results are globally correlated with the clustering results; based on the correlation clustering results, the corresponding multi-target tracking motion state processing is executed to obtain the transverse pendulum angular velocity; and based on the target motion state, the target size information as well as the heading angle information are updated.
Abstract:
A method for calculating an altitude of a target through an apparatus for calculating an altitude of the target, which comprises a plurality of MIMO radar virtual antennas, may comprise: receiving electromagnetic waves reflected from the target through a pair of virtual antennas classified into an upper antenna and a lower antenna and alternately arranged in two columns linearly; obtaining range information and phase information of the target from the pair of virtual antennas by analyzing the electromagnetic waves; and calculating altitude information of the target from position information of the pair of virtual antennas, and the range information and the phase information.
Abstract:
Various embodiments of the present technology generally relate to systems, methods, and computer-readable media for simulating synthetic aperture radar (SAR) images to be captured by a radar-based imaging system. SAR technology can be used to capture large areas on Earth, from a satellite in space for example, over a single pass. A further pass over the target area can help identify changes in the landscape, scenery, and/or infrastructure providing insight on change detection, temporal analysis, or other measures; however, repeat passes over the target area may have been made from differing angles resulting in artifacts in one or both of the processed images from the two passes. In various embodiments, information about the topology of the target area, and information about the SAR platform's flight path are used to simulate the slant range distortion effects that are to be expected in the SAR image of for that pass.
Abstract:
A radar apparatus for obtaining a higher range resolution than conventional radar apparatus without increasing the bandwidth comprises a transmitter antenna that transmits a frequency modulated transmit signal having a transmit bandwidth and a receiver antenna that receives a receive signal reflected from said scene in response to the transmission of said transmit signal. A mixer mixes said receive signal with said transmit signal to obtain a mixed receive signal, a sampling unit samples said mixed receive signal to obtain receive signal samples from a period of said receive signal, and a processor processes said receive signal samples by defining a measurement matrix and determines the positions of one or more targets of the scene by applying compressive sensing using said measurement matrix and said receive signal samples. A post-processor groups together receive signal samples having a depth within the same depth bin and belonging to the same target.
Abstract:
A radar apparatus for obtaining a higher range resolution than conventional radar apparatus without increasing the bandwidth comprises a transmitter antenna that transmits a frequency modulated transmit signal having a transmit bandwidth and a receiver antenna that receives a receive signal reflected from said scene in response to the transmission of said transmit signal. A mixer mixes said receive signal with said transmit signal to obtain a mixed receive signal, a sampling unit samples said mixed receive signal to obtain receive signal samples from a period of said receive signal, and a processor processes said receive signal samples by defining a measurement matrix and determines the positions of one or more targets of the scene by applying compressive sensing using said measurement matrix and said receive signal samples. A post-processor groups together receive signal samples having a depth within the same depth bin and belonging to the same target.
Abstract:
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.
Abstract:
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 pre-pulse 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.
Abstract:
Methods and apparatuses for processing measurements to create an interferometry-based metric to measure inaccuracy of a model. The metric is used as a cost function for nonlinear inversions or simplified linear inversions or imaging.
Abstract:
A method for locating a target comprises: a) receiving, by means of N≧1 receivers, opportunity radioelectric signals transmitted by M≧1 transmitters and reflected by the target, with N·M≧3, or at least one transmitter being situated out of sight of at least one receiver; b) receiving, by means of a data transmission link, one or more reference signals, representative of the radioelectric signals transmitted by each transmitter situated out of sight of at least one receiver; and c) determining the position of the target on the basis of the radioelectric signals and of the reference signal or of the reference signals. An application of the method to the primary monitoring of air traffic, a multistatic radar system for the implementation of the method, and a system for monitoring air traffic comprising a multistatic radar system are provided.
Abstract:
In one aspect, a method to generate radar signatures for multiple objects in motion, includes performing a shooting and bouncing (SBR) technique to solve for physical optics and multi-bounce characteristics associated with the objects. Performing the SBR technique includes performing dynamic ray tracing to form an image of an object having surfaces and edges. Performing the dynamic ray tracing includes transforming the object in a common coordinate frame of reference to a centered-body axis frame of reference.