101 results about "Passive radar" patented technology

The invention relates to the technical field of sea surface target multi-mode fusion recognition, in particular to a multi-mode fusion sea surface target recognition method of a high-dynamic unmanned platform. According to the method, a multi-modal fusion recognition framework based on a multi-kernel learning method is provided, and a small-sample multi-modal fusion target recognition algorithm for a sea-surface target is designed on the basis of the multi-modal fusion recognition framework. Target detection and feature extraction are respectively performed according to data characteristics of different sources of visible light images, SAR images and active and passive radar one-dimensional range profile signals, multi-mode heterogeneous features are mapped by using a multi-scale kernel method, weighted fusion of a kernel matrix is performed, global training optimization is performed, and finally a classification result of each sample can be output. The algorithm not only considers the performance of a data-driven target recognition algorithm, but also considers platform hardware computing power limitation and small sample conditions, so that the balance among the performance, computing power and samples can be realized.

The invention provides a passive radar seeker anti-interference identification method based on a dual-polarization array, and the method comprises the steps: obtaining a first signal and a second signal, and carrying out the time-space alignment calibration of the first signal and the second signal, and obtaining a first polarization signal and a second polarization signal; performing polarization-Doppler-frequency band three-dimensional tensor construction on the first polarization signal and the second polarization signal; performing dynamic core tensor decomposition processing on the polarization-Doppler-frequency band three-dimensional tensor to obtain a target polarization characteristic parameter and an interference polarization characteristic parameter; performing interference suppression processing on the first polarization signal and the second polarization signal through polarization matched filtering to generate an anti-interference enhanced signal; performing polarization scattering mechanism decomposition processing on the target polarization characteristic parameter to generate a target surface scattering component and a dihedral angle scattering component; and outputting an anti-interference identification result based on the target surface scattering component, the dihedral angle scattering component and the polarization phase consistency parameter of the anti-interference enhancement signal. The method can improve the anti-interference recognition precision of the radar.

The invention provides an AI-based passive radar multi-source electromagnetic positioning matching method and system, and relates to the technical field of artificial intelligence, and the method comprises the steps: firstly obtaining a multi-source electromagnetic signal data set of a target region, the multi-source electromagnetic signal data set is electromagnetic radiation signals synchronously captured by a plurality of signal collection devices in a preset time window, and the electromagnetic radiation signals are acquired by a plurality of signal collection devices; secondly, performing feature extraction on the multi-source electromagnetic signal data set to obtain a signal feature set containing signal intensity distribution, frequency domain correlation and time-space correlation features, then fusing the signal feature set based on a dynamic weight distribution strategy to generate a multi-dimensional positioning feature set, and then calling an AI positioning matching model to analyze positioning parameters to obtain a multi-dimensional positioning feature set; and obtaining a spatial position and a signal propagation parameter of the target electromagnetic radiation source. And finally, a positioning optimization instruction is generated according to the parameters and is fed back to the signal acquisition device cluster for parameter calibration, so that the electromagnetic positioning precision and reliability can be improved.

The invention discloses a vital sign and consciousness condition monitoring system based on active and passive radars, which adopts a low-sidelobe high-gain high-sensitivity double-frequency receiving antenna to receive millimeter wave echo signals and brain wave signals on the basis of monitoring vital signs by the existing millimeter wave radar, namely Ka wave band and brain wave band signals can be received. Meanwhile, an extremely-low-frequency (brain wave band signal frequency band: 0-20MHz) high-sensitivity receiver is additionally arranged in the high-sensitivity receiver module and is used for receiving and conditioning brain wave radiation signals, and then sampling, analyzing and processing are carried out in the signal processing module; the analysis and processing data result is compared with the analysis and processing data result, stored by the data storage module, of the normal person, and when the difference is larger than a threshold value, it is indicated that the vital signs or consciousness conditions of the patient are abnormal, and an early warning signal is sent out. The non-contact monitoring system is based on active and passive radars, vital sign signals and electroencephalogram signals are accurately collected, real-time, continuous and dynamic monitoring of vital signs and consciousness conditions of a patient is achieved, and therefore rapid rehabilitation of the patient under the good rest condition is facilitated.

The invention relates to an improved constraint weighted least square TDOA / FDOA passive positioning method based on a Lagrange multiplier, and belongs to the field of passive radar positioning. The method comprises a two-step method and comprises the following steps: firstly, converting a time difference and frequency difference nonlinear positioning equation about a target position and speed in a passive positioning problem into a pseudo-linear equation, on this basis, converting into a quadratic programming problem, simplifying constraint conditions, and solving a position and speed initial solution of target positioning by applying a Lagrangian multiplier method; and then a nonlinear equation set about the target position and the speed is constructed according to the original constraint condition, and the initial solution obtained in the first step is substituted into the constructed nonlinear equation set to further carry out optimization solution on the target position and the speed value. The method has good positioning precision and real-time performance, an estimation RMSE curve of a target positioning parameter can still be close to CRLB in a large-noise environment, and the method has good robustness in a high-noise environment and has good advancement.

The invention relates to the technical field of target detection and identification, and discloses a low-altitude target identification system and method combined with multi-band signal processing. Comprising the steps of establishing a cross-frequency implicit vector model and constraining a geometric scale, a scattering center and rotor harmonic waves through synchronous acquisition of an L-band radar, a Ku-band radar and a millimeter-wave radar, and realizing unified characterization of multi-frequency signals; receiving a global satellite navigation system reflection signal, communication channel state information or a very high frequency / ultrahigh frequency passive radar signal to form prior discrimination, and triggering high-frequency radar short-time imaging; carrying out propagation correction on millimeter wave, terahertz and infrared signals in combination with a meteorological profile and generating an environment label; determining a sampling window by using the region of interest and rotor phase prediction, and optimizing a residence strategy; harmonic waves are extracted from radar and acoustic signals, robust pairing is carried out, and a cross-domain consistency score output category is calculated. The method realizes multi-frequency multi-source cooperative processing, has environment self-adaption and closed-loop feedback capabilities, and can improve the precision and stability of low-altitude target identification.

The invention discloses a radar signal intelligent sorting method based on a GraphGated graph convolutional neural network, relates to the radar signal intelligent sorting method based on the GraphGated graph convolutional neural network, and belongs to the field of information and communication engineering. The objective of the invention is to solve the problem of difficulty in signal sorting of unknown signal sensing in a high-pulse-density environment, complex inter-pulse signal modulation and transient conditions of a current passive radar, an electronic reconnaissance radar, a cognitive radar, frequency spectrum situation sensing and the like. The method comprises the following steps of: 1, assuming that V pulse description words are received within time T; 2, constructing an adjacent matrix A based on the V preprocessed pulse description words, and constructing a radar pulse description word graph marked with node category attributes based on the adjacent matrix A; 3, obtaining a trained graph convolution model; 4, acquiring B to-be-tested pulse description words, and outputting feature vectors of the B pulse description words based on the trained model; and obtaining a clustering result through a clustering algorithm.

The invention provides an interval adaptive signal detection method and system based on a digital channelized receiver, and belongs to the field of signal detection in passive radars. The problems that in the passive radar signal receiving process of an existing digital channelized receiver, aliasing of signals and broadband noise exists, and power gains of different frequency bands are unequal, so that channelized signals cannot be normally detected are solved. The amplitude and phase information of M paths of signals are obtained by designing a filter bank, performing multiple serial-parallel conversion processing on input data and performing IFFT operation and CORDIC operation on data output by filtering K paths, then m-point self-correlation accumulation is performed on the amplitude of the M paths of signals, and the amplitude and phase information of the M paths of signals is obtained. Meanwhile, a more flexible threshold calculation method is provided, the working and signal detection bandwidth of the channelized receiver is refined, and a new scheme is provided for improving the signal detection adaptivity of the digital channelized receiver. The method is suitable for signal detection in a scene with non-uniform interference and gain distribution in the working bandwidth of the receiver.

The invention relates to the technical field of wind power plant echo suppression, in particular to a method for analyzing the multipath scattering effect of an offshore wind plant on a passive radar system, and the method comprises the steps: constructing a novel sea condition offshore wind plant model; the offshore wind plant model comprises a model construction module, a simulation position design module and a sea condition program application macro module; calculating scattering superposition RCS of different wind turbines in the wind power plant under different incident angles based on the offshore wind power plant model; constructing a multipath scattering mathematical model of the offshore wind power plant according to the offshore wind power plant model and scattering superposition RCS of different wind turbines in the wind power plant; the multipath influence of the offshore wind power plant on the passive radar system is confirmed based on the multipath scattering mathematical model of the offshore wind power plant, and the method is of great significance to scientific estimation of the passive radar system by the multipath scattering effect of the wind power plant.

The invention provides an unmanned aerial vehicle cooperative area coverage flight path optimization method and device and electronic equipment, and relates to the technical field of unmanned aerial vehicle flight path optimization, and the method comprises the steps: analyzing and obtaining flight path control parameters of each unmanned aerial vehicle in a flight path segment in an unmanned aerial vehicle formation, the flight path control parameters comprise a flight distance, a yaw angle variation and a maximum relative position distance between the two unmanned aerial vehicles; acquiring the interception probability of the passive radar system on the radio frequency signal of the unmanned aerial vehicle; establishing a radio frequency stealth-oriented track optimization model based on the track control parameters and the interception probability; improving a particle swarm optimization algorithm; and solving the track optimization model based on an improved particle swarm optimization algorithm. The radio frequency stealth performance of the unmanned aerial vehicle formation is effectively improved.

The invention relates to the technical field of sea surface target multi-mode fusion recognition system design, in particular to a multi-mode fusion sea surface target recognition system for a high-dynamic unmanned platform. The system is characterized by comprising a platform sensor subsystem, a multi-mode characteristic processing and identification subsystem, an information transmission control subsystem and a far-end display control subsystem, the system is combined with a corresponding sea surface target image feature extraction technology, an active and passive radar signal feature extraction technology and a sea surface target identification technology of a multimode heterogeneous feature fusion multi-core classifier, so that an efficient fusion identification system of four modal data of an optical image, an SAR image, an active radar signal and a passive radar signal is realized; according to the method, the high-dynamic unmanned system can autonomously judge the type of the sea surface slow-moving target, the multi-mode feature fusion utilization efficiency is enhanced, the target recognition precision and robustness are improved, and the autonomy and intelligence level of the high-dynamic unmanned system is improved.

The invention discloses a passive radar target positioning method and system based on an external radiation source, and relates to the technical field of radar positioning, and the method comprises the steps: screening an external radiation source signal set of a target monitoring region, laying a distributed receiving antenna array based on the signal set, receiving a signal in real time, and transmitting the signal to a quality evaluation unit; the quality evaluation unit adaptively screens the signal and outputs a standard radiation source signal with a radiation source type identifier; and carrying out feature parameter extraction on the standard signal to obtain a multivariate signal feature set, and carrying out multi-band signal fusion and target positioning analysis based on the feature set to generate target position information. According to the invention, the technical problems of complex signal processing, insufficient positioning precision and limited dynamic monitoring capability of the existing passive radar technology in a complex electromagnetic environment are solved, and multi-band signal fusion and adaptive signal processing are realized. And the positioning precision and the dynamic monitoring capability of the passive radar in a complex environment are improved.

The invention discloses an integrated low-slow-small unmanned aerial vehicle passive detection system and a working method thereof, and the system combines conventional radio detection and external radiation source detection technologies, and is composed of a broadband antenna, a receiver and a signal processor. The system can monitor the low, slow and small unmanned aerial vehicle in real time, and realizes the functions of direction finding, positioning, monitoring and the like of the unmanned aerial vehicle and the unmanned aerial vehicle pilot. The system fuses signal information acquired by radio detection and external radiation source detection technologies to form more accurate and more comprehensive unmanned aerial vehicle target information. And the target information of the unmanned aerial vehicle is displayed in real time through the display control equipment. Radio detection positioning and passive radar detection are combined, advantages are complementary, the false alarm rate is reduced, and reliability and accuracy are improved; the method is integrally realized, a hardware system is shared, software is used for parallel processing, the cost is reduced, the flexibility is improved, and the method is suitable for low-slow small unmanned aerial vehicle detection under multiple scenes and tasks.

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.

The application relates to an ionosphere virtual height estimation method applied to a short-wave active-passive integrated radar, which comprises the following steps: 1: an integrated detection system receives active radar detection echoes and passive radar detection echoes, and a main-passive detection channel is respectively subjected to distance, speed and azimuth sorting to obtain an active radar point track measurement set and a passive radar point track measurement set; 2: a group of points is respectively taken out from the two measurement sets, and the ionosphere virtual height is calculated by assuming the points as matched points; 3: the active radar measurement and the passive radar measurement are converted to the northeast sky coordinate system according to the calculated ionosphere virtual height; 4: a threshold method is used for global matching on the converted measurement sets to obtain a matching result, and a cost function value is calculated according to the matching result; 5: the two measurement sets are respectively traversed, and the steps 2, 3 and 4 are repeated, and the ionosphere virtual height corresponding to the minimum cost function is taken as the ionosphere virtual height in a detection environment. The application is used in the field of high-frequency over-the-horizon radar signal processing.

The invention provides a target reconstruction method and system based on passive sensing radar echo signals, and the method comprises the steps: obtaining a passive sensing radar echo signal set of a target scene, the passive sensing radar echo signal set comprising a plurality of echo signal sequences; performing signal preprocessing operation on the passive sensing radar echo signal set to obtain a preprocessed radar echo signal set; multi-level feature extraction operation is executed on the preprocessed radar echo signal set, a multi-dimensional state feature set of the target object is generated, and the multi-dimensional state feature set comprises scattering characteristic features, motion correlation features and environment interference suppression features; and calling a pre-trained target state analysis model to carry out state transition modeling processing on the multi-dimensional state feature set, generating a reconstructed state vector of the target object, and carrying out reverse mapping based on the reconstructed state vector to obtain a geometric parameter set and a motion parameter set of the target object.

The present invention discloses a system and method for dynamically optimizing passive detection resource parameters based on spectrum monitoring, which respectively controls spectrum monitoring resource resident parameters and passive detection resource resident parameters based on mission data, radar reception signals and spectrum monitoring data, and periodically optimizes passive detection resource resident parameters based on spectrum monitoring results and in combination with a spectrum knowledge base after receiving and processing radio frequency signals by a passive radar system. The dynamic optimization of passive detection resource parameters in the scheme of the present invention can customize search resource parameters according to the external environment to improve the probability of search and retention of intercepted targets; at the same time, when tracking the searched and intercepted targets, the tracking resource parameters and the tracking target parameters are dynamically adapted to improve the stability of target tracking.

The present invention discloses a method for estimating the direction of arrival of a coherent signal, belonging to the field of ship radar and communication signal processing. The method comprises: a transmitting end sends a pilot signal of a target power to a receiving end, and the receiving end obtains the multipath delay structure of the channel based on the pilot signal; the transmitting end sends a normal pilot signal to the receiving end, and calculates the cross-correlation function between the received signal and the transmitted signal; the peak values ​​of the cross-correlation function are sorted in descending order to determine the candidate possibilities of the first delay, and the cross-correlation function after the composite path is calculated to determine the shortest delay; a cost function for the delay is constructed, and the cost function is differentiated with respect to two independent variables to obtain an estimated value of the arrival time difference; the direction of arrival is calculated from the estimated value of the arrival time difference, completing the one-dimensional direction of arrival estimation of the coherent signal applied to a uniform linear array. This method can improve the detection accuracy of passive radar and sonar equipment for targets and enhance the comprehensive detection capability of surface ships.

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 present invention discloses a passive networked radar target detection method based on waveform characteristics, belonging to the field of target identification technology. The method includes obtaining a collected direct wave signal and a reflected wave signal to be detected; reading a historical database containing prior information of several historical direct waves and their emission source signals; searching the historical database for the historical direct wave with the highest similarity to the direct wave signal, and using the prior information of its emission source signal as the prior information of the direct wave signal; selecting a detector based on the prior information, inputting the direct wave signal and the reflected wave signal into the detector for detection, and outputting detection information; comparing the detection information with a preset detection threshold. If the detection information is greater than the detection threshold, a target is present; if the detection information is less than the detection threshold, a target is not present. This solution solves the problem of low target detection accuracy in low signal-to-noise ratio environments in existing networked passive radar target detection methods.

The invention discloses a UWB (Ultra Wideband) positioning method, device and equipment, relates to the technical field of communication, and can utilize broadcast signal frames of a plurality of base stations and mobile equipment in an information interaction process to form a condition of a passive radar to perform supplementary positioning verification on a position obtained by positioning calculation so as to improve the accuracy of UWB positioning. The method comprises the following steps: in the process of information interaction between a plurality of base stations and mobile equipment, acquiring broadcast signal frames received among the plurality of base stations, judging whether the broadcast signal frames carry reflected signals or not, if so, determining position change information of the mobile equipment according to the change condition of the reflected signals, and performing supplementary positioning verification on the position obtained by the positioning calculation of the mobile equipment by using the position change information of the mobile equipment so as to update the position of the mobile equipment.

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 present invention discloses a method and system for identifying slow-moving targets on the sea surface carried by an unmanned aerial vehicle based on passive radar signals. The shipborne search radar, which is the main electromagnetic radiation source of typical slow-moving targets on the sea surface, is used as the source for the passive radar to obtain electromagnetic radiation signals. Based on the radar parameters and operation modes of ship targets, the passive radar signals of typical sea surface targets are simulated through a simulation method. On this basis, a passive radar signal sample library of typical slow-moving targets on the sea surface is established to obtain the sample basis for data-driven target recognition. Furthermore, the sample signals are input into the target recognition system at the backend of the passive radar system to achieve the recognition of typical targets, that is, the identification of target categories. The present invention can provide advanced technical guidance for the construction of intelligent target recognition methods and systems driven by large samples, help expand the perception channels of slow-moving targets on the sea surface of unmanned aerial vehicle platforms, and enrich the means of battlefield reconnaissance and target surveillance.

The invention provides a passive radar secondary peak suppression method and device and electronic equipment, and can be applied to the technical field of passive radar signal processing. The method comprises the steps that a reference signal from an opportunity emission source and an echo signal from a detection target are acquired through a passive radar, and the echo signal is formed by reflecting a signal of the opportunity emission source by the detection target; detecting the signal format of the reference signal to obtain a signal format detection result; and performing secondary peak suppression on a coherent accumulation result of the passive radar based on the reference signal and the echo signal by using a processing strategy corresponding to the signal format detection result to obtain a target coherent accumulation result, the coherent accumulation result being determined based on the reference signal and the echo signal.

A sensor network for detecting an object includes an active radar component that detects the object by transmitting a radio signal and receiving an echo of the radio signal, a passive radar component that receives ambient radio waves from stationary emitters detects the object based on a reflection of the ambient radio waves off the object, and a sensor fusion device. The active radar component detects an electromagnetic interference signal emitted by the object provides an estimation of a direction of arrival of the interference signal. The sensor fusion device receives data from the active radar component and data from the passive radar component to perform a fusion of the data from the active radar component and the data from the passive radar component, and, based thereon, detect the object.

The present invention relates to the technical field of external radiation source radar positioning, and specifically to a low-altitude target positioning method for 5G external radiation source radar based on particle filter, which includes the following steps: S1, signal synchronization between the transceiver stations; S2, echo signal processing; S3, establishment of the target state transition model and measurement model; S4, particle initialization; S5, calculation of the pseudo-range error between the target and the transceiver stations; S6, particle weight update; S7, particle resampling; S8, target state extraction. The present invention uses a positioning method based on time difference to obtain pseudo-range information, takes the pseudo-range error between the target and the 5G base stations and receiving stations participating in the positioning as the measurement value, obtains the preliminary positioning and pseudo-range information as prior information by processing the received echo signal, constructs the target state transition model and measurement model, estimates the position of the target to be measured through the particle filter algorithm, and finally realizes target positioning, reducing the influence of clutter and interference on target positioning in the low-altitude complex environment.

The present invention discloses an anti-jamming method based on data association of a primary / passive radar combined seeker, which mainly solves the problems of large computational amount, high equipment cost and great influence by environmental factors in the prior art. The implementation scheme is as follows: the primary / passive radars respectively perform tracking filtering on the target to obtain state estimation values and error covariance matrices; the state estimation values and error covariance matrices of the active radar are converted into the polar coordinate system; track association is performed on the filtering data of the primary / passive radars in the polar coordinate system; the types of jamming are identified according to the track association results and decision conditions; when not being jammed, the data after primary / passive fusion is used for guidance, and when being jammed, the data of the passive radar is used for guidance. The present invention can effectively identify the types of jamming, reduce the probability of the seeker being deceived, improve the tracking accuracy of the target, and can be used for the tracking guidance of a primary / passive combined system seeker.