34 results about "Passive radar" patented technology

A frequency estimation method based on time-delay sampling is suitable for signal processing in an engineering scene in which leaf end timing, nondestructive testing or passive radar is difficult to deploy a high-sampling-rate or multi-sampling-rate system, and comprises the following steps: uniformly sampling signals by using two channels with the same sampling period; the time delay and the sampling period of the two sampling channels are relatively prime; carrying out Hilbert transformation preprocessing on data points of the two sampling channels, and solving aliasing frequency in cooperation with an ESPRIT algorithm; changing the initial position of the analysis data to construct a plurality of delay schemes, and repeating the step S2 to obtain equivalent sampling frequencies and equivalent aliasing frequencies under different delay schemes; according to the equivalent aliasing frequency, calculating two remainder frequencies under each delay scheme; and performing traversal solution on the congruence equation set with the equivalent sampling frequency as the modulus and the remainder frequency as the remainder by using the Chinese remainder theorem, and obtaining the target frequency in combination with the consistency criterion and the minimum estimation criterion.

This invention discloses an adaptive tracking method and device for anti-dropped decoys based on a multi-model approach to measurement errors, belonging to the field of radar target tracking technology. The method includes constructing motion and centroid interference models for passive radar dropped decoys to determine the impact of interference on radar measurements; constructing a set of passive radar measurement models characterizing the time-varying characteristics of measurement noise, and establishing a hybrid system with uncertain measurement noise by combining the target motion model; employing an interactive multi-model architecture combined with a capacitive Kalman filter algorithm to perform interactive and parallel filtering on each sub-model of the hybrid system; updating the posterior probability of the measurement noise in each sub-model at the current moment in real time based on the measurement residuals and information covariance; and performing weighted fusion of the state estimates of each sub-model to obtain the adaptive tracking result. This invention effectively solves the tracking divergence problem caused by weak observability and time-varying measurement errors in passive radar under dropped decoy interference, significantly improving the tracking accuracy and robustness of the system.

The invention discloses a weak cyclostationary signal detection method based on an unmanned aerial vehicle-mounted passive radar network, and the method comprises the steps: firstly building an active radar transmitting signal and unmanned aerial vehicle passive radar receiving signal model, and then building a binary hypothesis model based on cyclostationary generalized likelihood ratio detection through block cyclic matrix approximation; and constructing generalized likelihood ratio test detection statistics and obtaining local detection results of the unmanned aerial vehicles under a colored noise background by using the cyclostationary characteristic of target echoes, finally fusing the local detection results of the unmanned aerial vehicles based on a Bayesian minimum risk criterion at a fusion center, and outputting global detection judgment. And a detection process of cyclostationary generalized likelihood ratio test-Bayesian minimum risk fusion is formed. According to the method, the detection statistics are constructed by using the cyclostationary characteristics of the target echoes, the global detection accuracy and robustness can be improved under the conditions of low signal-to-noise ratio and complex colored noise, and the method is suitable for a multi-unmanned aerial vehicle cooperative passive radar detection scene.

The application discloses a passive radar network signal cooperative complementary sorting method and system, wherein the method comprises the following steps: cooperatively complementing mixed alias radiation source pulse sequence signals received by multiple passive radar stations to obtain complemented pulse sequence signals; and sorting the complemented pulse sequence signals by using a cumulative difference histogram method to separate pulse sequences of different radiation sources. Compared with an existing single-station passive radar signal sorting method, the method solves the problem of incomplete pulse sequences caused by pulse loss, greatly improves the correctness of signal sorting, and has better sorting performance, especially when pulse loss is serious.

The invention discloses a multi-base passive radar weak target detection method based on multi-channel space-time joint accumulation, and relates to the technical field of radar communication, and the method comprises the steps: constructing a multi-base passive radar system observation model, obtaining a direct wave signal and an echo signal, and carrying out the sampling and preprocessing of the direct wave signal and the echo signal; constructing a target detector, and updating the target detector into a simplified form expressed by the target motion parameters to obtain a first target detector; processing the first target detector by adopting a signal framing processing mode to obtain a second target detector; and processing and solving the second target detector by adopting a standard discretization mapping mode so as to realize detection of the weak target and obtain an estimation parameter of the weak target. According to the method, on the premise of ensuring relatively low calculation complexity, efficient collaborative accumulation of multi-channel signals is realized, and the detection performance of the system in a low signal-to-noise ratio and high maneuvering target environment is improved.

The utility model provides a head-mounted display device, and the device comprises a passive radar which is used for measuring an electromagnetic signal in an environment, so as to generate electromagnetic environment data; the control device is in communication connection with the passive radar and is used for acquiring the electromagnetic environment data and generating an electromagnetic image according to the electromagnetic environment data; and the display device is in communication connection with the control device and is used for acquiring and displaying the electromagnetic image so as to realize visual expression of the electromagnetic environment. According to the head-mounted display device, the passive radar is arranged, so that the head-mounted display device can monitor the electromagnetic environment and visually display the electromagnetic environment, the use function of the head-mounted display device is expanded, and the attraction to consumers is improved.

The application discloses a multi-radar joint positioning method based on azimuth angle and Doppler velocity, and mainly solves the problems of poor positioning precision caused by large sensor measurement error and insufficient utilization of multi-source data. The method is aimed at a sea surface target moving at a constant speed, and uses target direction finding results of 1-2 fixed passive radars and target Doppler velocity measurement values of 1 fixed ground wave active radar. According to different numbers of radars, different filter initial values and covariance matrices are constructed, corresponding measurement equations and different filter starting times are determined, and filtering is performed on the target state according to the constant speed motion model. The filtering output is used as the positioning result of the target. The method uses the measurement of passive radars and ground wave radars of two different systems, reduces the influence of large single measurement error on the positioning result, shortens the positioning time, and improves the positioning precision.

The application provides a radiation source positioning method and device based on distributed passive radar, the method comprising: acquiring a first linear frequency modulation signal intercepted by a plurality of receiving stations distributed at different positions and a second linear frequency modulation signal intercepted by a reference receiving station; determining a coarse time difference measurement value of the receiving station relative to the reference receiving station by using a correlation method based on the first linear frequency modulation signal and the second linear frequency modulation signal corresponding to the receiving station; calculating a time domain phase difference between the first linear frequency modulation signal and the second linear frequency modulation signal to determine a time difference error value of the receiving station relative to the reference receiving station; determining an accurate time difference value of the receiving station relative to the reference receiving station; and determining spatial position coordinates of the target radiation source according to the accurate time difference value corresponding to each receiving station. Through the method and device, the finally solved spatial position coordinates of the target radiation source are more accurate and stable.

The application is aimed at the channel allocation problem of the passive radar when tracking the maneuvering target, and a channel allocation method based on a new maneuvering target tracking accuracy prediction function for passive radar is proposed. By analyzing the deficiency of the existing IMM algorithm in the calculation of the target tracking accuracy prediction function in the processing of the mutual information between models, the size of the variance between models is considered in the proposed tracking accuracy prediction function to balance the perception sensitivity to target maneuvering and the accuracy of tracking performance prediction, and a new IMM-based PCRLB (IMM-PCRLB) is realized as a target tracking accuracy prediction function. Further, an optimization problem (MSCA) model of minimizing the channel usage under the constraint of expected tracking accuracy is established, and a heuristic algorithm based on contribution degree is designed for solution. The simulation results show that the algorithm proposed in the application can more accurately predict the actual tracking error, achieve the expected accuracy with reasonable channel resources in the maneuvering scene, and effectively alleviate the problem that the expected tracking accuracy cannot be met due to the inaccuracy of the objective function.

The invention relates to a frequency selective passive radar echo intensifier, and relates to the radar field, the frequency selective passive radar echo intensifier comprises a Luneberg ball, a reflection layer attached on one side of the Luneberg ball far away from the electromagnetic wave incidence direction, and a spherical shell-shaped skin layer wrapping the Luneberg ball and the reflection layer, the reflection layer comprises a substrate layer and an FSS layer, the multiple cross-shaped FSS layers are embedded between the two substrate layers at intervals so as to control the resonant frequency, and selective reflection is carried out on the frequency of part of radar waves. Meanwhile, the reflection intensity of radar waves with frequencies not specified by users can be reduced, so that the reflection intensity of the radar waves with the frequencies specified by the users can reach the highest intensity in common radar wavebands, or the specific requirements of the users can be met by implementing inverse-law echo enhancement on the radar waves with specific frequency bands; and the application range of the passive radar echo intensifier in the field of characteristic simulation systems is expanded.

This invention discloses an adaptive differential evolution algorithm for optimizing passive radar station deployment, comprising the following steps: establishing a passive time difference station deployment simulation scenario; step 2: population initialization; step 3: fitness value calculation; step 4: genetic operation. On the one hand, this invention addresses the problem of numerous variable parameters and complex parameter settings in particle swarm optimization (PSO) algorithms by incorporating iteration counts, fitness values, and weights into parameter generation, making the algorithm's search and convergence more reasonable. On the other hand, this invention considers the impact of station location error, time difference error, and communication distance between observation stations on the deployment results during experimental simulation, making the modeling process more realistic.

The application discloses a kind of passive radar multi-shot DOA estimation method and device based on sparse convex optimization, method includes obtaining the array receiving signal corresponding to the original input signal of multi-shot;Based on compressed sensing method, the problem of original input signal angle of arrival estimation is converted into l 2,th Sparse recovery convex optimization problem; 2,th Sparse recovery convex optimization problem by using hyperbolic tangent function instead of l 2,0 Mixed norm sparse recovery optimization problem in the l0 norm model is obtained;l 2,th Sparse recovery convex optimization problem in the l 2,th Mixed norm model is optimization goal, with the product of dictionary matrix and original input signal equal to array receiving signal as constraint condition;Iterative solution l 2,th Sparse recovery convex optimization problem obtains original input signal;And according to original input signal and dictionary matrix, the angle of arrival estimation value corresponding to original input signal is obtained, so as to improve the estimation accuracy and estimation efficiency of angle of arrival by effectively using multi-shot data.

The utility model relates to radar technical field, proposes a kind of passive radar conformal antenna array, comprising: outer panel, the one side of outer panel is fixedly installed with foam layer, the one side of foam layer is fixedly installed with function layer, the one side of function layer is fixed with bottom panel, the inside of foam layer, function layer is provided with helical antenna, the one side of helical antenna is fixedly installed with antenna receiving surface, the outside of helical antenna is fixedly installed with signal amplifier, the one side of antenna receiving surface is fixedly installed with heat dissipation shell, the inside of heat dissipation shell is fixedly installed with TR component. The shape of outer panel, foam layer, function layer and bottom panel is all set as arc panel, which can facilitate the installation of passive radar conformal antenna array on aircraft, thereby ensuring the aerodynamic performance of aircraft. The conformal antenna is designed integrally with the carrier surface, which can effectively reduce the radar reflection area RCS, thereby improving the stealth performance.

This invention discloses a passive radar moving target detection method based on low-Earth orbit (LEO) internet satellite radiation sources. Applied to the field of passive radar moving target detection, it addresses the problem of difficulty in acquiring satellite signals due to non-cooperation when using LEO internet satellites as radiation sources. This invention first acquires the direct wave and echo signals from the LEO internet satellite; then, it performs synchronization preprocessing on the direct wave signal to obtain the synchronization sequence; next, it demodulates both the direct wave signal and the target echo signal into the OFDM symbol domain; within this symbol domain, it calculates the correlation between the direct wave and target echo signal matrices; then, through signal processing of the correlation calculation results, it extracts the target bistatic distance and Doppler information from the correlation results; finally, it completes target detection based on this information.

A passive radar system and method of detection of low-profile low altitude targets based on the application of Low Earth Orbit (LEO) and Very Low Earth Orbit (VLEO) satellite signals. The staring array of directional antennas covers the entire sky and provides continuous illumination (receiving reflected satellite signals) from multiple targets for fast detection, recognition, and target tracking and increasing detection range. The coupling of each directional antenna with a separate receiver channel allows the fast continuous process of information from all targets simultaneously. Monopulse processing of signals from reference sub-set of antennas with overlap antenna patterns provides the highest directing accuracy and better clutter / noise and media influence suppression. A directional antenna array does not need a beam-forming module. The system has a small weight, and size may be portable or mounted on a light vehicle or small drone because small size and weight.

One example includes a passive radar receiver system including an RF receiver front-end to receive a wireless source signal and a reflected signal. An antenna switch of the front-end switches a first antenna to a receiver chain during a first time to generate first radar signal data based on a combined wireless signal comprising wireless source signal and the reflected signal, and switches a second antenna to the receiver chain during a second time to generate second radar signal data based on the combined wireless signal. A signal processor generates source signal data associated with the wireless source signal based on the first and second radar signal data and generates reflected signal data associated with the reflected signal based on the first and second radar signal data, and generates target radar data associated with a target based on the source and reflected radar signal data.

The application discloses a passive radar target positioning method and system based on external radiation sources, and relates to the technical field of radar positioning. The method comprises the following steps: screening external radiation source signals of a target monitoring area, and arranging a distributed receiving antenna array based on the signals; real-time receiving signals and transmitting the signals to a quality assessment unit; the quality assessment unit adaptively screens the signals, and outputs standard radiation source signals with radiation source type identification; characteristic parameters of the standard signals are extracted, a multivariate signal feature set is obtained, and multi-band signal fusion and target positioning analysis are carried out based on the feature set, so as to generate target position information. The application solves the technical problems of complex signal processing, insufficient positioning accuracy and limited dynamic monitoring capability of existing passive radar technology in a complex electromagnetic environment, achieves the technical effect of improving the positioning accuracy and dynamic monitoring capability of passive radar in a complex environment through multi-band signal fusion and adaptive signal processing.

The application discloses an anti-deception jamming method based on networked radars, which comprises the following steps: configuring networked radar systems as virtual isomorphic networking radar mode, virtual multi-base radar mode and virtual active / passive radar mode respectively; obtaining the anti-deception jamming success rate of the virtual isomorphic networking radar mode; obtaining the anti-deception jamming success rate of the virtual multi-base radar mode; obtaining the anti-deception jamming success rate of the virtual active / passive radar mode; selecting the mode corresponding to the maximum value among the anti-deception jamming success rates of the virtual isomorphic networking radar mode, the virtual multi-base radar mode and the virtual active / passive radar mode as the final mode. In the process of establishing the multi-station radar, the application can ensure that radars with multiple functions and systems are deployed at the same time, overcome the shortcomings of the existing single multi-station radar system, and meet different anti-jamming performance requirements.

The invention discloses an airborne radar radiation startup and shutdown judgment method based on a positioning and tracking root mean square error, and relates to the technical field of active and passive airborne radar cooperative detection, and the method comprises the steps: carrying out the parameter initialization, and presetting an RMSE threshold value; obtaining a passive positioning position of the target at the current moment by using a TDOA positioning algorithm at the current moment; based on the passive positioning position and the target motion model at the current moment, predicting a predicted value of target positioning tracking RMSE at the next moment, and comparing the RMSE predicted value with an RMSE threshold value to generate a startup and shutdown judgment result at the next moment; and according to a judgment result, selectively starting an active radar and fusing active and passive data at the next moment, or only utilizing a passive radar to track so as to obtain the final position of the target. By introducing a predictive RMSE judgment mechanism, unnecessary power radiation of the radar can be remarkably reduced on the premise of ensuring accurate positioning and tracking of the target, so that the utilization rate of radar resources is effectively improved, and the probability of being found is reduced.

The application discloses a combined tracking passive radar fluctuation target detection method and belongs to the field of radar target detection. In view of the nonlinearity problem of the measurement equation under the passive radar system, the volume Kalman filter is adopted to update the posterior state of the fluctuation target in the current frame, and the posterior state of the current frame is used to predict the prior state of the next frame, and the prior state is used as the support set prior information for reconstructing the range-Doppler image of the next frame. A dynamic extension orthogonal matching pursuit method is adopted to determine the selection range of the target support set by using the prior state information of the target in the current frame. When the target tracking information accurately generates the target RD image, the CKF is adopted to track the motion of the fluctuation target under the passive radar system, and higher approximation accuracy is provided. The application is suitable for the field of radar target detection, can accurately reconstruct the RD image of the fluctuation target, and improves the continuous detection performance of the fluctuation target under the passive radar system.

The invention discloses a multi-radar collaborative optimization station distribution method based on an improved particle swarm algorithm, and belongs to the technical field of radars. The method comprises the following steps: constructing a passive time difference positioning model comprising an active radar station and a plurality of passive radar stations; the active radar station is a radar station capable of emitting electromagnetic waves and is located at the origin of coordinates, the passive radar station does not emit the electromagnetic waves, and the station distribution position of the passive radar station is a position to be solved; constructing a target function by taking the minimum sum of the positioning errors of the passive radar stations in the flight airspace of the to-be-tracked target as a target; and solving the station distribution position of each passive radar station based on the objective function and the improved particle swarm optimization. According to the invention, efficient and accurate target positioning and tracking are realized.

1. The name of the design product: intelligent passive radar. 2. The use of the design product: detecting low-altitude flying unmanned aerial vehicles and other aircraft. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view.

A passive radar system for point-to-point directional communications comprising at least one Luneburg lens antenna.

A method of determining the location of a physical object using a passive radar receiver includes determining if a transmitter beam sweeping period (TBSP) is known, and executing a TBSP-based receiver beam sweeping if the TBSP is known. If the TBSP is not known, determining if the TBSP can be measured, and executing the TBSP-based beam sweeping if the TBSP can be measured. The method includes executing a random receiver beam sweeping if the TBSP is not known and cannot be measured. The method includes determining a relative time of arrival of radio signals between the LoS path and the target path, and determining the propagation times on the LoS path and on the target path. The method includes determining the location of the physical object using the propagation times.

A method for monitoring an offshore installation (102) using a passive radar (100) is proposed. The method comprises illuminating an area around the offshore installation (102) with at least one first polarized signal (108a) and one second polarized signal (108b) by means of a transmitter on a movable platform (110). The method further comprises receiving the first polarized signal (108a) and the second polarized signal (108b) and receiving a first reflected signal (112a) and a second reflected signal (112b), wherein the first reflected signal (112a) is a reflection of the first polarized signal (108a) from an object (114) and the second reflected signal (112b) is a reflection of the second polarized signal (108b) from the object (114).The object (114) is classified based on the first polarized signal (108a), the second polarized signal (108b), the first reflected signal (112a), and the second reflected signal (112b). A trajectory of the object (114) is determined. An alarm signal (120) is issued if the trajectory meets a defined condition and if the object (114) belongs to a defined class.

The application provides an ESM and PCL integrated fusion detection system, comprising: an ESM and PCL integrated radio frequency signal processing device, which is used for detecting a radiation source in a target area to obtain radiation source information, receiving a reflection echo signal of a target object based on a center frequency point of the target radiation source provided by a display control device, determining a first baseband signal based on the reflection echo signal, and providing the first baseband signal to the display control device; and the display control device, which is used for displaying a radiation source list based on the radiation source information, determining the target radiation source in the radiation source list, providing the center frequency point of the target radiation source to the ESM and PCL integrated radio frequency signal processing device, and performing PCL passive radar target detection processing on the first baseband signal to obtain detection information of the target object. The ESM and PCL integrated fusion detection system provided in the application is used for improving the detection accuracy of the target object.

The application discloses a direct-path interference suppression distributed passive radar signal-level robust positioning method, comprising the following steps: S1, system parameter initialization; S2, establishing a double-channel observation model of the distributed passive radar; S3, constructing a high-dimensional multi-parameter target position optimization problem based on monitoring channel observation; S4, constructing an external radiation source signal estimator based on reference channel observation; S5, constructing a signal-level low-complexity high-precision robust target position estimator combined with monitoring channel and reference channel observation, and acquiring the maximum likelihood estimation of the target position through multi-stage grid search. The estimator designed by the application can realize signal-level low-complexity high-precision robust target positioning in a direct-path interference environment, and can be applied to target positioning of the distributed passive radar and the like.

This invention discloses a method for multi-target localization and micro-motion sensing using a bistatic multi-channel passive radar. The method includes: first, matrix reconstruction and smoothing preprocessing of the bistatic signals, followed by estimation of the number of signal sources using an improved MDL algorithm; second, addressing multipath and strong interference issues by identifying multipath sources through matrix reconstruction and employing an interference blocking algorithm to suppress strong interference and extract weak target signal angles; third, matching bistatic angles using frequency correlation criteria, combined with direction-finding cross-location and DBSCAN clustering algorithms to achieve accurate multi-target localization; and finally, inverse angle deduction and echo extraction based on the localization results, followed by phase noise elimination through conjugate processing to achieve target micro-motion feature sensing. This invention effectively improves the detection and localization accuracy and feature extraction capability of passive radar for multiple targets in complex environments, and has strong engineering practicality.

The invention discloses a multi-mode radar signal rapid implementation method based on GPU multi-stream processing, which is suitable for real-time signal processing of active, passive and active and passive mixed radar modes, and performs parallel processing on radar echo data through a GPU multi-stream processing mechanism by depending on GPU parallel computing capability and a cuFFT special acceleration library. The CPU host end constructs a circular queue and adopts multiple threads to realize in-dequeue non-interference parallel, and after UDP data receiving, frame verification and mode classification are completed, valid data are copied to a GPU video memory through a PCIE bus; the GPU side accelerates core algorithms of all modes in parallel through corresponding streams, active radar pulse compression, moving target detection, passive radar clutter cancellation, distance Doppler processing and the like are achieved respectively, two kinds of stream processing are started synchronously in the mixed mode, and finally a detection result is transmitted back to the CPU and displayed in real time through a UI interface. According to the method, the multi-mode radar signal processing efficiency is effectively improved, the problems of multi-mode data interference and processing delay are solved, and the real-time processing requirement is met.

The application discloses a passive radar target echo simulation system, comprising: a radio frequency signal generator, a power division unit and an amplitude and phase control unit connected in sequence; a total control unit connected with the radio frequency signal generator and the amplitude and phase control unit; the total control unit is used for analyzing the received control command, obtaining the passive radar working parameters and target parameters, and converting the passive radar working parameters and target parameters into first control instructions and second control instructions; the radio frequency signal generator is used for generating a reference microwave signal according to the first control instructions; the power division unit is used for dividing the received reference microwave signal into N microwave signals; the amplitude and phase control unit is used for receiving the second control instructions, adjusting the output amplitude and output phase of the N microwave signals according to the second control instructions, and then outputting the N microwave signals after being combined, and the application solves the problems of small instantaneous bandwidth and low simulation precision of multi-target echo characteristics.