61 results about "Multistatic radar" patented technology

A real-time signal processing engine robustly detects, localizes, tracks and classifies ground targets based on radar signals from a multistatic radar system. The system differentiates between different targets based on an optimized cost function, which can include the total returned normalized pulse energy. The local transmitters/receivers can communicate with each other via the transmitted radar signals.

The invention discloses a microwave optical fiber link device for long-distance transmission of radar reference frequency signals and relates to the technology of radar detection. The microwave optical fiber link device consists of an optical emitter, an optical receiver, a Faraday rotating mirror, an optical circulator, a polarization maintaining optical fiber, a radio-frequency power amplifier and the like. By subjecting microwaves to electric-optical and optical-electric conversion and utilizing the advantages of low insertion loss and high-temperature phase stability of the optical fiber, the microwaves are transmitted in low phase fluctuation and loss in the long distance. The microwave optical fiber link device can be used for transmission of rate-aided signals of spatial long-base line interference synthetic aperture radar (SAR) and transmission of reference frequency signals of radar systems such as phased array radars and multi-base radar monitoring net. Besides, phase changes caused by environmental factors such as temperature and irradiation can be accurately compensated during long-distance transmission of X-wave band microwave signals, and meanwhile, the microwave optical fiber link device has ultrawide radio-frequency (RF) working band and can be developed for transmission of radar reference frequency signals ranging from 50MHz to18GHz.

The invention relates to a human body recognition method based on multi-base radar micro-Doppler and a convolutional neural network, and belongs to the technical field of radar target recognition. According to the method, the multi-base radar is used so that the echo signal difference caused by the change of view can be alleviated, the recognition robustness can be enhanced and the recognition accuracy can be enhanced. The convolutional neural network is applied to perform data processing without manual feature design so as to have certain universality and excellent recognition accuracy performance. According to the method, the transfer learning technology is used, the RGB optical image is utilized in the convolutional neural network to pre-train the weight and the three-channel multi-resolution time-frequency graph having the similar RGB optical image is used as the input of the convolutional neural network so that the pre-training weight dimension is matched, more information is provided in comparison with that of the single-resolution time-frequency graph. Great recognition accuracy can be obtained in multiple human body recognition tasks by the method.

Aspects of this invention are directed to the substantially improved detection and geolocation accuracy of targets (stationary or moving) by using the coherent data received at multiple airborne sensors. Further aspects are directed to aligning the (unknown) time-delayed and Doppler-shifted signals received at the multiple sensors relative to an arbitrary reference sensor, which depend on the unknown target position. This results in the target position and velocity vectors being simultaneously estimated and the detection peak enhanced by obtaining near coherent gain. Still further aspects are directed to the coherent generalized likelihood ratio test (GLRT) and the minimum variance distortionless response (MVDR) statistic for multistatic radar systems, conditioned on estimation of certain parameters that render the system coherent. Analytical and computer simulation results are presented to show substantially enhanced detection and geolocation of moving targets in clutter.

The invention discloses a method for achieving three-dimension positioning of a non-cooperative double multistatic radar target. The method belongs to the technical field of passive double multistatic radar target positioning. In a non-cooperative double multistatic radar, an existing target position estimating method based on the iterative optimal algorithm has the defect that due to the non-linear relationship between a target position and double base parameters, if the initial value is not properly selected, a wrong solution can be obtained and in addition, the iterative algorithm consumes lots of time. Thus, the invention provides the method for obtaining an analytical solution of a three-dimension position of the non-cooperative double multistatic radar target. The method integrates measuring of multiple pairs of transmitters and receivers and deduces the analytical solution of the three-dimension position of the target through a model of minimal target position error vectors of the target position. The method for achieving three-dimension positioning of the non-cooperative double multistatic radar target is fast in arithmetic speed, suitable for a double multistatic radar system to perform target positioning, wherein the double multistatic radar system carries out opportunity detecting based on all sorts of opportunity illuminators. Initiation of a target track is facilitated and a better result can also be obtained under the multiple-target environment.

The method comprises: 1) designing a multiple antenna transmitting drive signal; 2) two dimensional modulation designing is made for said signal; 3) encoding the message to be transmitted; 4) the signal is modulated and transmitted; 5) making carrier extraction and coherent demodulation for the received signal. The invention not only has PSK and QPSK digital communication capacity, but also can make high accuracy direction finding like mono-pulse radar, and is a new architecture of bistatic radar or multistatic radar.

The invention discloses a fast fluctuating target dual threshold constant false alarm detection method based on a multistatic radar. The method comprises steps: 1, echo data are collected; 2, the collected echo data are subjected to square law detection; 3, according to the data after square law detection, a local test statistic is calculated; 4, a first threshold is calculated, the local test statistic is judged according to the first threshold, if the local test statistic is larger than the first threshold, the local test statistic is transmitted to a fusion center, or otherwise, elimination is carried out; 5, according to the local test statistic transmitted to the fusion center, a global test statistic is calculated; and 6, a second threshold is estimated, the global test statistic is judged according to the second threshold, if the global test statistic is larger than the second threshold, existence of the target is judged, or otherwise, the target is judged not to exist. The radar target can be effectively detected, the system is simple, the applicability is wide, and the method can be used to improve the multistatic radar target detection performance.

The invention discloses a double-threshold constant false alarm detection method under clutter subspace based on a multistatic radar, mainly to solve the problems of complex calculation, low detectionperformance and the like in the prior art. The method comprises steps: 1, echo data are collected; 2, the collected echo data are subjected to generalized likelihood ratio detection to obtain a localdetection statistic amount; 3, a first threshold is calculated, the local detection statistic amount is judged according to the first threshold, if the local detection statistic amount is larger thanthe first threshold, the local detection statistic amount is transmitted to a fusion center, or otherwise, elimination is carried out; 5, according to the local detection statistic amount transmittedto the fusion center, a global detection statistic amount is calculated; and 6, a second threshold is calculated, the global detection statistic amount is judged according to the second threshold, ifthe global detection statistic amount is larger than the second threshold, existence of the target is judged, or otherwise, the target is judged not to exist. The radar target can be effectively detected, the system is simple, the applicability is wide, and the method can be used to improve the multistatic radar target detection performance.

The invention discloses a particle filter centralized tracking method for multi-base radar out-of-sequence measurement fusion, which belongs to the technical field of data fusion of multi-base radar systems. According to the invention, out-of-sequence measurement is sequentially used to update all states between the out-of-sequence measurement generation time and the latest sequential filter time,and particle filtering is used to achieve target tracking; the problem of deterioration of target fusion tracking performance, which is caused by radar measurement out-of-sequence caused by differentdata processing time of a radar station and communication link delay, is overcome; whether the current measurement is sequential measurement is judged; if the current measurement is sequential measurement, sequential measurement update is carried out, and otherwise out-of-sequence measurement fusion is carried out; the problem of out-of-sequence measurement of multiple arbitrary timing sequences,which is caused by different data preprocessing time of each radar station and communication link delay in a multi-base radar system is effectively solved; and a universal solution is proposed for the problem of out-of-sequence measurement of multiple arbitrary timing sequences, which has higher fusion precision than direct neglect of out-of-sequence measurement.

The invention relates to the field of radio, aims at solving the problems of flight path measurement of a low-slow-small unmanned aerial vehicle target and beam synchronous scanning of multi-static radar, and discloses a low-slow-small unmanned aerial vehicle flight path measurement system and method. The system comprises monitoring equipment, a transmitting station, receiving stations, a data processing center and data transmission links. The number M of the monitoring equipment is greater than or equal to 2 and the monitoring equipment is used for measuring the radiation signal and the direction of the unmanned aerial vehicle. The data processing center determines the target area of the unmanned aerial vehicle and guides the transmitting station and the receiving stations to synchronously point to the target area. The transmitting station and the receiving stations are respectively configured in the middle and the periphery of a protective area, wherein one set is configured in the middle and at least two sets are configured at the periphery. The receiving stations only receive and process the echo signal of the target area. The data transmission links complete transmission of data, command and reference signals. The low-slow-small unmanned aerial vehicle flight path measurement system and method can be applied to the airport clearance protective area and the large oil depots and other key protective areas.

The invention discloses a bistatic/multistatic radar image PS (permanent scatterer) point associating method based on a sliding scattering center, which accurately registers multiple SAR images viewed from different angles, and belongs to the field of bistatic/multistatic synthetic aperture radars. The method comprises: obtaining an approximate target outline scattering function by performing parabolic fitting on a PS point target outline function in a bistatic image; obtaining a homonymy point in a monostatic radar image by performing moving window search on the monostatic radar image; and finally, registering the monostatic radar image according to the homonymy point obtained through the search. The method fully utilizes the characteristics of the sliding scattering PS point target, solves a puzzle that a conventional PS point registering method is just capable of accurately registering images observed from a single angle, and has significant meaning to multi-angle radar image fusion and interference processing.

The invention discloses a multistatic radar sea small target detection method, which comprises the following steps: a shore-based transmitting unit transmits an electromagnetic wave signal to a targetsea area; multiple airborne receiving units receive echo signals reflected by the target from different directions respectively; and each airborne receiving unit processes echo signals, the target isdetected and target position information is generated. According to the multistatic radar sea small target detection method, the shore-based transmitting unit is adopted to transmit the electromagnetic wave signal, and the multiple airborne receiving units receive the echo signals reflected by the target from different directions. The transmitting unit is arranged on the shore to provide large enough transmission power to increase the detection distance, the receiving unit adopts multiple airborne platforms to solve the problem that the small target RCS violently fluctuates with an observation angle, the target RCS is ensured not to be at the minimum at the same time, and the sea small target detection probability is improved.

The present invention discloses a distributed batch estimation fusion method for an asynchronous multistatic radar system. Firstly, an update cycle is set according to a sampling rate of a local radar and an actual requirement of data updating, a particle filtering algorithm is used to carry out local filtering at a multistatic radar, a local posterior estimation result and a local prediction density function of the multistatic radar in the update cycle are obtained, then a Gauss approximation model is used to approximate the local posterior estimation result and the local prediction density function as Gauss distribution, communication is carried out among multiple radars to exchange corresponding Gauss parameters, finally an alignment strategy of using a target state transfer characteristic to carry out recursion to carry out alignment of asynchronous Gauss parameters of the multiple radars, and the distributed batch estimation fusion method is used to fuse the aligned Gauss parameters. According to the method, a problem that the asynchronous data of a synchronous multistatic radar is difficult to fuse can be effectively solved, the calculation quantity of the fusion process is low, and the fusion precision is high.

The invention discloses an anti-multistatic radar detection camouflage metasurface construction method. The method comprises the following steps: determining physical quantities representing target characteristic quantities at different radar observation angles; a metasurface is dispersed into a plurality of regulation and control modules in space, each regulation and control module is used for regulating and controlling radar echoes, and a dispersion angle is set according to the size of an actual regulation and control module array and the electric size of a metasurface unit; the metasurface units are utilized to establish each regulation and control module, and the metasurface is regulated and controlled to change the target characteristic quantity according to the inclination angle between the regulation and control modules and the physical quantity under different radar observation angles; beam deflection of harmonic waves is realized by changing the starting time of a time sequence between each row of units of the regulation and control module, so that the whole camouflage metasurface realizes feature camouflage in a set observation angle interval. The method has the advantages of being simple, efficient and flexible, and camouflage can be achieved at multiple observation angles in the space.

The invention discloses a multi-static radar active false target identification method and system. The method comprises the steps: obtaining a receiving signal vector of a target, wherein the target is obtained through the detection of a multi-static radar; calculating a correlation coefficient between every two targets according to the received signal vectors; performing clustering analysis on the target according to the correlation coefficient; and identifying a clustering analysis result by adopting threshold detection to obtain a clustering category, and acquiring whether each target in the cluster is an active false target according to the clustering category. According to the invention, the problem that the existing multi-static radar anti-deception jamming method cannot be applied to multiple jamming sources can be solved.

The invention provides a multi-emission-source passive locating method based on position and waveform parameter joint estimation, and relates to the field of radar signal processing. According to themethod, locating of multiple emitters for emitting unknown linear frequency modulation signals is considered, and a multistatic radar receiver is adopted to intercept and capture the signals and transmit data to a processing center for locating. The method comprises the steps of firstly, using short-time Fourier transform to obtain a time-frequency spectrum of the received signals, then conductingHough transform on the time-frequency spectrum to separate and extract the time-frequency spectrum, then using a basic sorting algorithm to process the separated time-frequency spectrum, and finally,determining positions and signal parameters of multiple emission sources through the further utilization of grid search. By means of the multi-emission-source passive locating method based on the position and waveform parameter joint estimation, aiming at multiple linear frequency modulation emitters, passive locating is effectively combined with short-time Fourier transform and Hough transform,and the signal parameters and the positions are jointly estimated while the increase of the calculation amount is controlled. The problem that it is difficult for an existing passive locating algorithm to locate multiple objects is effectively solved, and thus high-precision locating of the targets is achieved.

The invention discloses an active false target identification method and system for a multi-static radar. The method comprises the steps of: obtaining received signal vectors of targets which are detected by a multi-static radar; calculating a correlation coefficient between every two targets according to the received signal vectors; performing clustering analysis on the targets according to the correlation coefficients; and identifying a clustering analysis result by adopting threshold detection to obtain the category of the cluster, and determining whether each target in the cluster is an active false target according to the clustering category. According to the method, the problem that the existing multi-static radar anti-deception jamming method cannot be applied to multiple interference sources can be solved.

The invention discloses a missile body analysis and positioning method based on a double/multi-base radar. The implementation scheme comprises the following specific steps: 1) establishing a three-dimensional imaging coordinate system; 2) acquiring an image of a missile-borne double/multi-base radar ground distance plane; 3) obtaining matching points in the missile-borne double/multi-base radar ground distance plane image; 4) calculating the total number of distance units of each matching point; 5) calculating the bistatic distance sum of the missile-borne bistatic/multistatic radar; 6) establishing a missile-borne double/multi-base radar nonlinear positioning equation set; 7) solving the position coordinates of the receiving radar in the missile-borne dual/multi-base radar; and 8) determine the position coordinates of the receiving radar in the missile-borne dual/multi-base radar. The missile-borne double/multi-base radar positioning method is used for positioning the receiving radarin the missile-borne double/multi-base radar in the missile terminal guidance stage, and has the advantages of being high in positioning precision, wide in application range and good in robustness.