73 results about "Radar signal detection" patented technology

A cruise control apparatus can control a host vehicle to run with a fixed separation from a preceding vehicle when such a preceding vehicle is detected based on received radar signals and to run at a preset fixed speed when no preceding vehicle is detected. The cruise control apparatus is configured to respond to one of a set of predetermined actions by the vehicle driver, which indicate an intention to change the vehicle speed, by making it easier or more difficult for a preceding vehicle to be detected, in accordance with whether the indicated intention may signify that an actual preceding vehicle is not being detected or may signify that a non-existent preceding vehicle is being detected and that the host vehicle speed has been reduced accordingly. Improved performance is thereby achieved by utilizing the cognitive abilities of the driver to augment the detection operation of the cruise control apparatus.

A wireless communication device includes a receiver circuit that receives a wireless signal. Here, the wireless signal includes a signal from a node in a communication network to which the wireless communication device belongs and a radar signal. The receiver circuit detects a received power of the wireless signal. The wireless communication device further includes a radar signal detection circuit, coupled to the receiver circuit, which determines if the wireless signal comprises the radar signal based on the received power of the wireless signal.

A method provides for identifying short radar signals in presence of interfering signals from various sources applicable to U-NII devices. The method includes collecting a set of information about received interfering signals until the End-Of-Burst (EOB) condition is identified. When the EOB is identified, the set information about the received train of interfering signals is processed. The algorithm selects the time interval between two pulses as a possible Pulse Repetition Interval (PRI) and checks if the same time interval or a multiple of it can be found between other pulses in the collected set, with some small acceptable error. Pulses matching the criteria are considered as potential radar pulses. When at least one pulse has been identified as a potential radar pulse for a number of times larger than a predefined limit, it is concluded that that pulse has been generated by a radar installation.

The invention provides a signal parameter real-time precision measurement method of a synthetic aperture radar (SAR) and belongs to the field of radar signal detection. The method integrates the digital channelized receiver technique and the phase difference instantaneous frequency measurement technique to achieve the real-time parameter measurement of the signals of the SAR; in consideration of the processing capacity of the processor and the hardware resources, the parallel processing method and the hardware resource time division multiplexing method are integrated to achieve the real-time processing of the huge data stream generated by the signals of the high-bandwidth high-timewidth non-cooperative SAR in the prior processor; the inherent error of the system time parameter is analyzed by use of the laboratory environment and the time parameter is compensated; and the transient response is avoided by utilizing the characteristics of the SAR signals and the frequency-domain parameter is correctd to obtain the accurate frequency-domain parameter. The method reduces the computation load, provides full consideration, achieves the real-time precision measurement of the signal parameters of the high-bandwidth high-timewidth non-cooperative SAR, and improves the real-time property and the precision of processing the high-bandwidth high-timewidth signals of the detection receivers in service.

A method, algorithm, architecture, circuits, and/or systems for robust radar signal detection for wireless communications are disclosed. In one embodiment, a method of detecting a predefined signal pulse event in a wireless network device can include the steps of: (i) comparing a power of a received signal pulse to a predetermined power threshold of a predefined signal; (ii) determining a duration of the received signal pulse when the power of the received signal pulse is greater than the predetermined power threshold; and (iii) indicating an occurrence of the predetermined signal pulse event when the duration of the received signal pulse is between first and second predetermined duration thresholds of the predefined signal. The predefined signal pulse event can be a radar signal pulse, for example. Embodiments of the present invention can advantageously provide a reliable and simplified approach for radar signal detection suitable for wireless network devices.

The invention relates to a hidden radar falling alarming method applicable to supervision and care of people who easily fall and applies to the technical field of medical care instruments. The methodcomprises steps as follows: a radar signal detection module transmits and receives a radar signal, and a signal processing and analysis module processes and analyzes the received radar signal and judges whether a falling phenomenon happens. A communication module transmits processed data and analysis results to a server, and these data can be stored in the server for a longer time. A client displays alarming information through a mobile phone APP, so that a guardian conveniently handle the falling condition, the guardian is not required to accompany a person at any moment, and the working intensity of the guardian is reduced.

The invention discloses a radar signal detection method based on a convolutional neural network. According to the method, a distance-Doppler frequency spectrum obtained after pulse Doppler processingis used as an image sample, different characteristics of a time-frequency spectrum with or without a target are taken as identification characteristics, radar signal detection is realized by utilizingthe classification capability of a convolutional neural network, existence of a target signal is judged, the convolutional neural network is applied to radar signal processing, and signal detection is realized from the perspective of image processing. Compared with a traditional CFAR detector, the method of the inventiom has the advantages that the detection probability is improved, the influencecaused by the correlation of background clutters when the CFAR detector is used is avoided, and the limitation that the fixed CFAR detector is suitable for a specific environment is improved.

The embodiment of the invention discloses a method and device for detecting asphalt pavement structure interlayer stripping. The method comprises the steps that a radar echo signal of a pavement to be detected is obtained by carrying out radar signal detection on the pavement to be detected; echo signal parameters of the pavement to be detected are obtained by carrying out data analysis on the radar echo signal; and interlayer stripping indexes of road segments of the pavement to be detected are obtained according to the echo signal parameters, and if it is known that the interlayer stripping indexes are within a preset range through judgment, it can be determined that the road segment corresponding to the interlayer stripping indexes suffer pavement structure interlayer stripping. The device is used for implementing the method. According to the method and device, due to the facts that the radar echo signal of the pavement to be detected is obtained by carrying out radar signal detection on the pavement to be detected, and the interlayer stripping indexes of the road segments of the pavement to be detected are obtained according to the radar echo signal, quick detection on the asphalt pavement structure interlayer stripping phenomenon is achieved, and the accuracy of detection on the pavement structure interlayer stripping phenomenon is improved.

The invention discloses a threatening radar signal detection method based on compressed sensing. The threatening radar signal detection method based on compressed sensing mainly solves the problems that during existing electronic reconnaissance, the sampling rate is high and detection is difficult under the signal parameter overlapping condition. The threatening radar signal detection method based on compressed sensing comprises the following steps of (1) generating an original radar signal sample space by means of a given threatening radar signal database, (2) establishing a redundant dictionary according to the sample space, (3) conducting sparse representation on signals to be detected, (4) conducting compressed sampling on the signals to be detected to obtain a low-dimensional observed value, (5) solving a sparse coefficient and (6) finishing detection of threatening radar signals. According to the threatening radar signal detection method based on compressed sensing, a compressed sampling method is introduced to the radar signal detection field, and radar signals overlapping in the aspects of time, space and frequency spectrums are effectively detected on the condition that the sampling rate is low.

The invention discloses an LPI radar signal detection method based on a CNN, and the method comprises the steps: carrying out signal detection through the CNN, converting a signal detection problem into a feature extraction problem based on the CNN, carrying out the sampling of intercepted radar signal pulses, directly inputting an in-phase component and an orthogonal component of a sampled discrete signal into a neural network, and realizing high-accuracy signal detection within a certain error range. According to the invention, the method has a generalization capability for LPI radar signaldetection under different SNRs; due to randomness of parameters such as signal bandwidth and carrier frequency, generalization of a test set can be ensured, which indicates that the method has certaingeneralization capability for untrained signals and has good application prospect.

The embodiment of the present invention discloses a method and device for asphalt pavement segregation detection. The method includes: performing radar signal detection on the road surface to be detected, acquiring the radar echo signal of the road surface to be detected; performing data analysis on the radar echo signal , to obtain the echo signal parameters of the road surface to be detected; according to the echo signal parameters, obtain the segregation evaluation factor of each road section of the road surface to be detected, if it is determined that the segregation evaluation factor is greater than a preset threshold, then determine the Pavement segregation occurs in the road section corresponding to the above segregation evaluation factor. In the embodiment of the present invention, by performing radar signal detection on the road surface to be detected, the radar echo signal of the road surface to be detected is obtained, and the segregation evaluation factors of each section of the road surface to be detected are obtained according to the radar echo signal, so as to realize the rapid detection of asphalt pavement segregation phenomenon, Improve the accuracy of pavement segregation detection.

The invention provides a radar signal detection method, a radar signal detection device, electronic equipment and a storage medium. The radar signal detection method comprises the steps of: performingpulse compression processing on an echo signal received by a radar; performing phase-coherent accumulation and clutter suppression processing on the signal subjected to pulse compression processing;carrying out constant false alarm detection on the signal subjected to phase-coherent accumulation and clutter suppression processing in a mode of combining a mean value type constant false alarm detection method and an ordered statistics constant false alarm detection method to obtain a detection result, wherein a threshold coefficient adopted during constant false alarm detection is a gradual change threshold coefficient, and the gradual change threshold coefficient comes from a threshold coefficient curve obtained by fitting a change trend of a signal-to-noise ratio of the echo signal alongwith the distance. The mean value type constant false alarm detection method and the ordered statistics constant false alarm detection method are complementary, and the detection probability is further improved. Through fitting of the threshold coefficient, optimization of the fixed threshold coefficient is realized, the false alarm rate is reduced, and the performance of the detection algorithmis greatly improved.

The invention discloses a radar signal detection data sample labeling method, and mainly aims to solve the problems of high requirement on the quality of labeling personnel, large workload and low working efficiency in a mode of analyzing and extracting radar data one by one mainly through manual labeling in an existing sample labeling method. The method comprises the following steps: extracting effective data through visualization software for labeling, and storing the effective data as a standard sample file; and taking the standard file as a template, traversing and collecting an original data file, and automatically generating a new sample file. The method has the advantages that personnel with rich radar signal detection data analysis experience can concentrate on manually labeling data appearing for the first time; similar target data selection can be matched by adopting a similarity calculation method, although calculation is time-consuming, the calculation can be automaticallyrealized by a computer, and a large number of data samples can be extracted without consuming extra manpower.

The invention discloses a road underground cavity detection early warning method based on deep learning and a ground penetrating radar. The method comprises the following steps: collecting a noisy ground penetrating radar echo signal of an actual road through the ground penetrating radar; filtering and smoothing the noise-containing ground penetrating radar echo signal to obtain a de-noised ground penetrating radar echo signal; performing augmentation processing on the de-noised ground penetrating radar echo signal by adopting a generative adversarial neural network to obtain a radar echo signal; and detecting the radar echo signal by using a fast regional convolutional neural network to obtain a first detection early warning result. According to the method, the GANs network is adopted to augment the underground hole data set, the problem that training samples are insufficient during underground hole detection based on deep learning is solved, meanwhile, the fast regional convolutional neural network model is adopted for detection, the learning ability of the network to signal features is improved, and the detection accuracy is improved. The deep learning technology is better applied to the radar signal detection technology, and nondestructive detection can be carried out on the road more accurately and quickly.

The invention belongs to the technical field of electronic reconnaissance, and particularly relates to a passive radar signal detection method based on sequential statistical filtering and binary detection. According to the invention, after certain speed reduction and signal-to-noise ratio improvement are carried out on low-signal-to-noise-ratio signals in a large instantaneous monitoring bandwidth through channelization preprocessing, binary accumulation detection is combined, and rapid and accurate detection can be realized under a certain low-signal-to-noise-ratio condition. The method adapts to the trend that the sampling rate of a reconnaissance system in the passive radar field is higher and higher, and solves the problem that signal detection is difficult under the condition of low signal-to-noise ratio. On the basis of a relatively stable condition in a channel, a detection threshold is estimated by performing sequential statistical filtering processing on reference data in a parallel sliding window without additional threshold compensation; wherein the parallel pipeline type structure ensures that an adaptive constant false alarm threshold can be quickly obtained under strong noise, the detection and false alarm probability can be further improved by adopting a binary accumulation detection technology, so that the application limitation of an existing detection method is overcome.

The invention provides a detection and interference integrated waveform generation method based on intermittent sampling, and the method comprises the steps: carrying out the optimization through employing an integrated signal Doppler ambiguity function side lobe peak value ratio and a ratio of a standard deviation to a mean value of amplitude after pulse pressure, and constructing a corresponding objective function; and solving the objective function by using a genetic algorithm to obtain an optimal amplitude coding mode. A fuzzy function is an effective tool for analyzing radar signal detection performance, and a linear frequency modulation signal is insensitive to Doppler frequency and high in sidelobe peak value. According to the integrated signal optimization design process, the extreme value is solved by changing a pulse amplitude coding sequence, the genetic algorithm takes the coding of decision variables as an operation object, takes an objective function value as search information, measures the excellence degree of individuals through a fitness function, and has good global search performance. Therefore, the objective function is solved by adopting a genetic algorithm. The integrated waveform signal generated by the invention has a certain detection function while interfering with a signal of an opposite side.