134 results about "Radar waveforms" patented technology

The invention relates to the technical field of radar waveform optimization, in particular to a synthetic broadband waveform optimization method based on reinforcement learning. According to the method, a deep reinforcement learning framework is adopted, and end-to-end optimization is carried out on the center frequency and amplitude parameters of multiple sub-pulses. The method comprises the following steps: constructing a synthetic broadband waveform signal model, and parameterizing sub-waveforms to determine a search space of an optimization problem; converting a waveform optimization problem into a reinforcement learning form, and defining a state space, an action space, a reward function and a state transition mechanism; based on a deterministic soft action value iteration strategy algorithm, point spread function features are extracted in combination with a Transform encoder, and sub-pulse parameters are dynamically adjusted. Through the method, the main lobe resolution can be effectively suppressed and improved, the target detection performance of a radar system is improved, and the method has good global optimization capability and environmental adaptability and is suitable for cognitive radar and adaptive waveform design scenes.

The invention provides a programmable frequency control array radar waveform generation system and method based on an FPGA, and belongs to the technical field of radar systems and digital signal processing. In order to solve the technical problems of complex hardware system, inflexible parameter adjustment and poor multi-channel synchronism of the traditional frequency control array radar, the invention provides an integrated high-performance solution. The system adopts an FPGA (Field Programmable Gate Array) architecture of an integrated processing system (PS) and programmable logic (PL). The method comprises the following steps: a PS end receives waveform control parameters of an upper computer through a communication interface and transmits the waveform control parameters to a PL end; and a plurality of parallel direct digital frequency synthesizer (DDS) modules in the PL end synchronously generate multi-channel digital baseband signals with programmable frequency offset at high precision according to the parameters under the unified driving of the FPGA global clock network. And the digital signal is subjected to digital-to-analog conversion and radio frequency front-end processing to finally form a transmitting wave beam. According to the invention, flexible programmability of parameters is realized by utilizing a PS-PL collaborative architecture, the synchronization precision of multi-channel signals is remarkably improved through a global clock network and a parallel DDS module generated in the FPGA, and meanwhile, the system has the advantages of high integration level and low complexity.

The invention discloses a radar waveform phase design method based on a KAN network, and relates to the technical field of radars, and the method comprises the steps: constructing an expected directional diagram covariance matrix based on a transmitting directional diagram according to the information of a transmitting antenna; constructing a combinatorial optimization objective function according to the expected directional diagram covariance matrix and the parameter waveform; inputting the waveform of the random initial phase sequence into the ResKAN network, and performing iterative optimization on the ResKAN network by taking the combinatorial optimization objective function as a loss function until iteration is finished to obtain an output waveform of the ResKAN network; the network input is respectively connected with the KAN residual module and the Vit coding module; the KAN residual module and the Vit coding module are respectively connected with the attention guidance fusion module; and the attention guidance fusion module, the nested KAN structure, the decoder and the network output are connected in sequence. When the radar waveform is designed, the calculation efficiency, the optimization precision and the implementation complexity are considered at the same time.

The present disclosure relates to methods and systems based on a new type of radar waveform, taking the form of a continuous aperiodic signal, effectively indistinguishable from white noise, though actually it is a signal allowing both accurate and ambiguity free range and radial velocity, i.e. Doppler, measurements.

The invention provides a joint optimization method and system for MIMO radar waveform design and antenna array arrangement, and belongs to the technical field of radar signal processing. A covariance matrix of a transmitting signal set is converted into a transmitting weight matrix of a time domain, and matching optimization of a radar waveform and an expected beam pattern is realized based on the transmitting weight matrix; according to the method, the directional diagram performance of the optimized radar waveform of the time domain in actual emission can be ensured, meanwhile, the influence of an antenna array arrangement vector on an emission beam pattern is considered, joint optimization is carried out on the radar waveform corresponding to an emission weight matrix and the antenna array arrangement vector, collaborative optimization between waveform design and array design is achieved, and the method has the advantages of being high in practicability and high in practicability. The overall performance potential of the system can be fully excavated, and the actual demand of a target detection task in a complex environment can be well met.

The invention provides a radar waveform optimization method, system and device, a medium and a program product, and the method comprises the steps: transmitting a basic radar signal employing a basic waveform, and receiving an original echo signal formed by the reflection of a target; extracting a radar cross-sectional area of a target from the original echo signal to obtain a target RCS; traversing an RCS allowable range corresponding to each target type in the feature database, and determining a matching result; determining waveform control parameters of the radar waveform; an optimized radar signal employing the optimized waveform is generated and transmitted. According to the scheme, traversal matching is carried out on the target radar cross-sectional area measured in real time and the RCS allowable range in the feature database, adaptive optimization of the radar transmitted waveform on the current target RCS is realized, in addition, the candidate PRF is systematically traversed in the PRF feasible range corresponding to the target type, and the target type is more accurate. The adaptive matching of the PRF parameter with the current target RCS and the propagation condition is realized.

The invention discloses a multi-frequency-band signal fusion microwave photon radar system and an implementation method thereof, and relates to the technical field of optical signal processing, and the system comprises a multi-frequency-band signal transmitting module which is used for generating a multi-frequency-band bandwidth radar signal; the m microwave photon dechirp receiving modules are used for receiving echo signals of three or more multi-band bandwidth radar signals in an optical domain; the multi-frequency-band signal fusion processing module is used for carrying out interpolation and filling of spectrum gaps on missing frequency bands among multiple frequency bands through a coherent fusion technology so as to realize fusion splicing of multi-frequency-band signals; m is the number of multi-band channels; according to the method, the broadband characteristic of the photon technology can be fully utilized, and the distance resolution of target detection is effectively improved under the condition that the bandwidth requirement of the radar waveform electrical generator is not increased through fusion processing of multi-band bandwidth radar signals.

The invention provides a geological anomalous body recognition method, system and device and a storage medium, and belongs to the field of radar waveform recognition, and the method comprises the steps: simulating and generating ideal scan images of a plurality of different geological anomalous regions, and building a geological anomalous scan image database; converting the actually acquired geological radar oscillogram of the geological abnormal area to obtain an actual scan image; inputting the actual scan image into a data engine, performing comparative analysis on the actual scan image and different ideal scan images through the data engine, and finding out an ideal scan image which is most similar to the input geological radar oscillogram in the aspects of features and forms from a geological anomaly scan image database; geological abnormal area information corresponding to the geological radar oscillogram is obtained through the found ideal scan image, and the type of the geological abnormal body is determined according to the geological abnormal area information. The geological anomalous body recognition accuracy is improved, and the type of the geological anomalous body is judged.

The invention relates to the technical field of radars, in particular to a low-interception-probability radar waveform design method and device, and the method comprises the steps: obtaining a preset MDP tuple; constructing a Markov decision model framework based on a preset MDP tuple, wherein the Markov decision model framework comprises a design framework corresponding to the power adopted for constructing a radar waveform and the complexity of a radar waveform intra-pulse modulation pattern; performing reinforcement learning on the Markov decision model framework in a strategy optimization direction taking maximization of long-term accumulated rewards as a target to obtain a reinforcement learning optimization model of radar waveform design; and solving the reinforcement learning optimization model of the radar waveform design by using a model-free Q-learning algorithm to obtain the design parameters of the radar wave, thereby realizing the intelligent design of the low-interception probability radar waveform in the complex electronic countermeasure environment, and improving the concealment and detection performance balance capability of the radar in the unknown countermeasure environment.

The application discloses a tunnel surrounding rock intelligent grading prediction method and system based on multi-modal space-time fusion, relates to the technical field of tunnel construction, and provides the following scheme, which comprises obtaining time-stamped surrounding rock multi-modal data, the multi-modal data comprising geological radar waveform data, drilling core images and three-dimensional laser point cloud data; a space-time fusion network architecture is adopted to generate surrounding rock feature data and perform tunnel surrounding rock grading prediction. According to the scheme, three types of multi-modal data, namely, geological radar waveform data, drilling core images and three-dimensional laser point cloud data, are fused to provide a comprehensive feature basis for surrounding rock grading prediction, a real-time feedback mechanism is constructed by introducing construction machinery vibration spectrum data, abnormal disturbance is identified by comparing a dynamic threshold library with historical data, vibration features and surrounding rock features are associated based on an LSTM network, accurate rock mass parameter correction amounts are generated, and space-time fusion network parameters are reversely optimized, so that the deviation between static prediction and actual geological conditions is effectively reduced.

The invention discloses a normalized deep reinforcement learning radar waveform design method, which comprises the following steps: modeling a radar confrontation environment based on a Markov decision process model, expressing a radar anti-interference problem as a Markov decision process with a limited field-of-view state space, determining a state, an action and a conversion dynamic state, and designing a normalized deep reinforcement learning radar waveform. Setting a reward function in the existing deep reinforcement learning algorithm; the beneficial effects of the invention are that the system stability and the learning efficiency are improved through the enhancement of the reward normalized discount; a radar environment is modeled as a Markov decision process, so that an agent can optimize a waveform strategy through interaction with a state space, an action space and a reward function; compared with an LFM method, a non-normalized D3QN method and the like, the method has the advantages that the signal to interference and noise ratio of a radar receiver end is increased, the target detection probability is increased, interference and clutter interference are effectively reduced, and an effective way is provided for automation and intelligentization of radar waveform generation in an anti-environment.

The invention relates to the technical field of water gushing monitoring, in particular to a tunnel water gushing dynamic control and safety monitoring method and system based on geological radar, and the method comprises the following steps: in the tunneling mechanical propulsion process, when the oil pressure drop rate exceeds a rate threshold value, determining a tunneling negative pressure period; acquiring a radar waveform dynamic sequence in the negative pressure time period; key feature parameters are extracted from the radar waveform dynamic sequence; marking a region which simultaneously meets the amplitude attenuation mutation rate and the phase deviation cumulant as a water gushing precursor target region; and by taking the water gushing precursor target region as a center, generating a conical diffusion preventive grouting field. According to the method, the dynamic sensing capability of the sudden water bursting risk is enhanced, the space-time continuity expression capability of the abnormal region is improved, and the precursor intensity can be quantitatively distinguished through the thermal value.

The invention, which relates to the radar simulation and electronic countermeasure field, provides a multi-mode broadband radar simulation electronic target system and method for an unmanned aerial vehicle, and the system comprises an upper computer, a ZYNQ signal processing module, an ADRV9009 radio frequency transceiver module and a transmitting module which are connected in sequence. According to the invention, a ZYNQ signal processing module and an ADRV9009 radio frequency transceiver module are taken as hardware bases, multimode radar simulation is taken as a software architecture, various radar waveforms are generated and adjusted according to key characteristic indexes of a radar, inter-pulse characteristics, intra-pulse characteristics and frequency tuning are supported, and radar signals in a complex electromagnetic environment are accurately simulated.

The present application relates to a MIMO radar multi-target detection method and system based on strong target restriction, which designs a beam weight matrix solving method with strong target restriction on the basis of a MIMO radar multi-target detection method based on reinforcement learning, takes out possible strong targets from the detection results of the MIMO radar, calculates the power gain restriction values corresponding to each strong target, designs a beam optimization scheme with strong target restriction and solves the beam weight matrix by using a convex optimization toolbox. During detection, the radar waveform corresponding to the transmission beam weight matrix is used, the Wald type statistics of the radar echo is calculated, the state calculation and action selection are performed, the angle unit to which the beam pattern of the MIMO radar needs to be focused is selected, and finally the beam weight matrix of the next detection time is quickly solved according to the beam weight matrix solving method with strong target restriction, so as to improve the detection performance of the MIMO radar on weak targets.

The application discloses an airborne radar downburst optimized detection method and belongs to the technical field of radar signal processing. An airborne Doppler radar is used to emit a radar waveform to a possible wind shear dangerous area in front of a route, and wind speed estimation in a transmission direction is obtained by analyzing radar echo IQ data. The application sets a pitch angle of radar scanning according to a take-off or landing stage of an airplane. After receiving the IQ signal, frequency domain correction is performed, data is preprocessed according to spectrum width information, and a wild value area is eliminated. After the preprocessing is completed, a frequency domain clutter suppression algorithm is used to suppress a ground clutter area near zero frequency, and then wind shear wind speed estimation is performed. The application proposes a novel vertical wind speed estimation model, establishes a connection between a downburst core area range and a vertical wind speed gradient, forms a detection and sensing capability for a three-dimensional area of the downburst, and proposes an airplane scanning strategy for optimizing the model.

Systems, methods, and computer-readable media for performing radar operations based on characteristics of a target. First operational limits defining a limit of a detection operation, imaging operation, or some combination thereof can be identified. The first operational limits can be associated with first operational values of operational parameters. Radar waveform parameters to optimize can be identified. Further, first optimal values for the radar waveform parameters can be identified based on the first operational values associated with the first operational limits. Additionally, a first optimized radar signal can be generated using the first optimal values of the radar waveform parameters. The first optimized radar signal can be optimized for the first operational limits. As follows, the first optimized radar signal can be transmitted towards a target area.

The invention relates to a joint radar communication system within a wireless communication environment, comprising: at least one processor; at least one transceiver configured to transmit a radar signal through which the azimuth data is transmitted with the radar waveform; at least one receiver configured to receive an echo of the radar signal; and at least one memory communicatively coupled to the at least one processor. The transceiver is configured to transmit a joint radar communication signal (JRC), and the receiver is configured to receive an echo of the radar signal using a joint radar communication channel and transmit a communication (JRC) signal.

The invention discloses an ocean laser radar waveform photonizing and post-pulse removing method. According to the method, single photon response calibration is completed by utilizing probability histogram distribution of single photon output integral values of a photomultiplier (PMT), and photonization processing of original echo waveforms acquired by the ocean laser radar is realized; and the post-pulse probability is calibrated to realize quantitative removal of the post-pulse. The experimental device comprises a signal generator, a laser, a digital adjustable attenuator, a photomultiplier (PMT), a data acquisition card and an upper computer processing module, and the stability of system triggering and data acquisition is ensured. According to the technical scheme, through single-photon calibration based on the integral value, continuous analog sampling and uniform representation of the photon number of discrete single-photon output waveform signals are completed, interference of post-pulse on weak signals of the ocean laser radar is eliminated, the measurement precision and reliability are improved, and the device has the advantages of being simple in structure, convenient to operate and accurate in calibration and has a wide application prospect. The method is suitable for the high-precision ocean laser radar detection field.

The invention relates to the technical field of radar signal level anti-interference, and discloses a coherent accumulation method for a radar waveform, and the method comprises the steps: obtaining a joint frequency repetition frequency agile waveform JFPAW echo signal in a distance frequency domain and an azimuth time domain; according to the calculated optimal coarse velocity, performing range migration compensation on the JFPAW echo signal; performing frequency Doppler compensation on the JFPAW echo signal according to the distance obtained after range migration compensation; and according to the non-uniform Fourier transform, calculating to obtain a coherent accumulation result of the JFPAW echo signal. According to the method, coherent accumulation of echo signals under the condition of phase random fluctuation caused by frequency and frequency domain agility is realized, and the low interception and anti-recognition capabilities of modern radars can be effectively improved. The invention further discloses a coherent accumulation device for the radar waveform and electronic equipment.

This invention discloses a robust waveform design method for uncertain sets of inter-pulse fluctuations of spherical targets. The steps include: selecting the radar waveform to be optimized and the filter size; modeling the target inter-pulse fluctuations and the transmitted waveform constraints to form an optimization problem; transforming the optimization problem into an equivalent problem and solving the equivalent problem to obtain the covariance matrix of the radar transmitted waveform; synthesizing the radar transmitted waveform using the obtained waveform covariance matrix, and solving the receiving filter based on the synthesized waveform. This invention provides a radar waveform design method that is robust to target inter-pulse fluctuations. This waveform, while ensuring magnitude constraints, fully utilizes prior information about target inter-pulse fluctuations, providing robust target detection performance under uncertain sets of spherical target fluctuations.

The embodiment of the application relates to the technical field of cognitive radar, and provides a cognitive radar constant modulus waveform design method and device based on maximum signal-to-clutter-noise ratio, the method comprising: obtaining a feedback signal echo obtained after a cognitive radar transmitting signal, wherein the feedback signal echo comprises a target echo component and a clutter echo component, the target echo component is output after the transmitting signal is convolved with a unit impulse response of a target, and the clutter echo component is output after the transmitting signal is reflected by a clutter scattering point; calculating a signal-to-clutter-noise ratio of an output signal after a matched filter based on the feedback signal echo; obtaining an optimal energy spectrum density of the transmitting signal when the signal-to-clutter-noise ratio is maximum under a preset energy constraint condition; and determining a target constant modulus signal waveform based on the optimal energy spectrum density. Therefore, the radar waveform is dynamically adjusted through the interaction between the radar and the environment, better adaptability is achieved in a complex clutter environment, the balance between time domain and frequency domain characteristics is maintained, and target detection performance is improved.

The present invention relates to a DAC-based pulse radar multi-waveform signal generation method, which belongs to the field of signal processing. The method can flexibly set various signal parameters, adopts a fully digital method to design and generate pulse radar signals in various relatively complex environmental scenarios, and realizes the generation of various pulse radar signal waveforms in the application environment, including frequency modulation (conventional frequency modulation, frequency diversity, frequency agility), frequency repetition rate (PRI) modulation (conventional, staggered, jitter, sliding, jumping), and intra-pulse modulation (intra-pulse single tone, linear frequency modulation, nonlinear frequency modulation, phase encoding, frequency encoding, and hybrid encoding). The method can simultaneously combine various pulse radar waveforms, dynamically adjust according to the DAC working data bit width, and generate corresponding signals according to the signal waveform output mode. The method has obvious advantages in the simulation generation of pulse radar signals in electromagnetic environments.

The invention relates to a radar agile waveform generation method and device, computer equipment and a storage medium, and the method comprises the steps: firstly obtaining a waveform parameter of a radar original waveform, searching a random code library constructed by a plurality of sequence random codes generated based on a plurality of preset encryption algorithms for a target sequence random code corresponding to the waveform parameter, and modulating the waveform parameter by using the target sequence random code to generate a radar agile waveform. According to the method, the target sequence random code is obtained from the random code library constructed based on multiple encryption algorithms, and the random code is highly random and unpredictable, so that the radar waveform signal generated by modulation has unique characteristics, interference can be effectively resisted, and the survivability of the radar in a complex electromagnetic environment is improved. Meanwhile, waveform parameters can be flexibly adjusted, the resolution for different targets can be remarkably enhanced, radar performance can be optimized, false alarm and missing alarm can be reduced, and stable and efficient operation of the radar can be ensured no matter for multi-target detection or complex scene imaging.

The application provides a radar waveform classification method and system based on effective area identification, and the method comprises the following steps: inputting a radar emitter time-frequency image into a preset SSD network trained in advance to obtain an effective area where a single intra-pulse signal is located and a corresponding radar waveform category output by the preset SSD network; the preset SSD network is trained by taking multiple radar emitter time-frequency images as training samples, taking the effective area where the single intra-pulse signal is located in each radar emitter time-frequency image and the corresponding radar waveform category as labels. The application identifies the effective area where the intra-pulse signal of the radar emitter time-frequency image is located by using the SSD network, and only classifies the category of the waveform in the effective area in the subsequent process, thereby avoiding the influence of signal characteristics in the invalid area on identification, and effectively improving the identification accuracy of the radar waveform.

This invention provides a three-dimensional radar vision inspection method and system. The method first performs two-dimensional image inspection on the target object to preliminarily determine its material properties, and then sends a first electromagnetic wave to the target object to perform three-dimensional modeling. Next, material parameters are assigned to the target model, and electromagnetic wave propagation simulation is performed to obtain a simulated radar waveform. Ray tracing measurements are then performed on the target object using radar to obtain a measured radar waveform. The simulated radar waveform and the measured radar waveform are compared. If the difference between the two is within a first preset range, the material of the target object matches the material corresponding to the assigned material parameters. If the difference is still within the first preset range, the material parameters are updated, and the above steps are repeated. This inspection method can not only acquire the three-dimensional morphological information of the target object but also determine its surface material properties, overcoming the limitations of existing technology systems and providing comprehensive object recognition and material analysis capabilities.

The invention discloses a sub-echo reflectivity correction method and system based on a B-spline model, and the method comprises the steps: firstly, fully quantifying the irregular features of a laser radar waveform signal through the B-spline model, improving the precision of multi-echo signal information interpretation in a complex environment, and providing reliable initial parameter support for the subsequent sub-echo reflectivity correction; then, by means of a distribution simulation algorithm and vegetation vertical structure distribution, ground and different vegetation target point clouds are classified into two types, and the two types are reflectivity correction algorithm priori knowledge; thirdly, deducing a reflectivity correction algorithm from a radar basic principle equation, and further deriving a multi-layer chain type correction equation; according to the method, the reflectivity of the multiple sub-echoes is further corrected from the standard ground reflectivity and the first target reflectivity correction, a single echo of a single vegetation target is not needed, the precision of a reflectivity correction algorithm is greatly improved, and the application range of the reflectivity correction algorithm is greatly widened.

The method for avoiding third-order intermodulation based on radar waveform generation of the application comprises the following steps: obtaining image test results under different radar parameters based on a standard radar test, adjusting the relationship of the different radar parameters by a frequency spectrum analyzer, determining the relationship between the pulse repetition frequency (PRF) and the frequency difference of different radar signals, and the radar parameters including the radar pulse repetition frequency and the frequency difference between different radar signals; suppressing the third-order intermodulation when the radar transmits and receives multiple signals; after suppressing the third-order intermodulation, sending the generated signal carrier frequency information to the radar radio frequency part, generating corresponding multiple signals and radiating. In a manner without reducing the signal-to-noise ratio, the influence of the third-order component is avoided, thereby improving the signal detection performance of the radar.

The present invention relates to the technical field of radar signal processing, and discloses a method for generating a radar anti-jamming waveform for a multi-time-scale coupled network. Its main contents include the generation of a transmitted waveform and the processing of an echo signal. First, a method for designing an orthogonal waveform for a MIMO radar is given. Then, the transmitted waveform of the MIMO radar for each channel is used as the input of the multi-time-scale coupled network, so as to generate a set of reference signal groups for broadband signal matched filtering. Finally, a method for processing the echo signal of the designed waveform is given. The purpose of the present invention is to design a MIMO radar waveform with good orthogonality and anti-jamming ability, generate a reference signal for broadband matched filtering using a multi-time-scale coupled network, and give a method for processing the echo; the transmitted waveforms between the sub-arrays of the MIMO radar should satisfy orthogonality so that the transmitted waveforms between the sub-arrays can be distinguished by matched filtering at the receiving end.

The invention relates to the technical field of radars, and provides a radar interference effect evaluation method, device and equipment based on small sample learning. And determining a plurality of different target type interference parameters corresponding to each preset type of radar waveform and a plurality of interference evaluation indexes in the plurality of preset type interference parameters. And determining a small sample task training set according to the plurality of preset type radar waveforms, the plurality of different target type interference parameters corresponding to each preset type radar waveform and the plurality of interference evaluation indexes. And training is carried out according to the small sample task training set and a Reptile meta-learning algorithm, and a radar interference effect evaluation model is obtained. The radar interference effect evaluation model is trained through the small sample task training set, so that the method can better adapt to scenes with scarce data or small samples during radar confrontation reconnaissance, the problems of weak generalization ability and poor robustness of the radar interference effect evaluation model are avoided, and a relatively accurate interference effect evaluation result is obtained.

The embodiment of the present invention discloses a detection and communication integrated signal processing method based on positive and negative frequency modulation, including: a radar system generates an integrated detection and communication waveform, the communication code element information is distributed to each transmission channel after serial-to-parallel conversion, and is mapped to the radar LFM waveform transmitted by each antenna, and the positive or negative frequency modulation slope of the generated LFM signal is determined by the value of the communication code element information; after each receiving channel of the radar system receives the target reflection echo, it is mixed with the corresponding transmitting array element carrier frequency difference and then subjected to bandpass filtering to separate the transmission signal of each channel, and the transmission signal of each channel is processed by communication signal processing and radar signal processing respectively to obtain a serial communication sequence of the communication transmitting end and the result of target detection. The technical solution provided by the embodiment of the present invention solves the problem that the existing integrated waveform solution is difficult to combine the performance advantages of low computational complexity, high communication transmission rate and spectrum utilization.