Abstract: Aiming at the issues of low angle estimation accuracy and long convergence time of radar seekers under low signal-to-noise ratio, a two-dimensional angle estimation algorithm for target tracking and detection based on field programmable gate array (FPGA) is proposed in this paper. The sum difference multi-channel joint filtering is adopted by this algorithm, and the angle information of the target is integrated into the state vector of the Bernoulli filter for recursive estimation while detecting. In order to shorten the processing time of angle estimation, the design of FPGA pipelining is adopted, and the calculation of “floating point+fixed point” and exponential classification are used for the calculation nodes that affect the accuracy of angle estimation to improve the accuracy of angle estimation. Through simulation and testing experiments, compared with traditional algorithms for tracking after detection, the proposed algorithm achieves better angle estimation performance. In addition, the processing time of a single frame of the proposed algorithm reaches the microsecond level, and the convergence time of angle estimation is short, which greatly improves the real-time performance of target tracking detection.
Abstract: In the field of autonomous driving, autonomous driving systems need to use sensors to detect the road environment, and then build high-precision maps to describe the environmental characteristics. All-weather adaptability, accurate range, and Doppler velocity measurement capabilities make millimeter wave radar a candidate for sensors in advanced driver assistance system applications, but there is currently little research on the elimination of moving targets in environmental mapping based on millimeter wave radar. Therefore, millimeter wave radar is used to dig deep into the Doppler information in the environmental point cloud data, and a radar grid mapping method based on four-dimensional point cloud is proposed. This method has the characteristic of directly eliminating moving targets in the mapping process, which can get rid of the dependence on sensors such as odometer and accelerometer, and has the advantage of not being affected by light and dust. It is suitable for environmental perception under complex weather conditions in the field of autonomous driving. Simulation results verify the practicability of the proposed method.
Abstract: In the context of information warfare, a comprehensive and accurate understanding of the battlefield situation is the key for commanders to make correct decisions. Situation generation refers to the estimation, understanding, and prediction of the situation based on the perception of battlefield elements, and forming situation products that meet operational needs. It plays an important role in the entire combat process, including detection, tracking, identification, strike, and evaluation. An overview of situation generation technology for sea battlefield is made in this paper. Firstly, the development process of situation generation is introduced, including the origin of concepts of situation generation, the evolution of basic models and the application of typical projects. Then, the understanding of the connotation of situation generation is elaborated, and the typical characteristics that high-quality situational generation should possess are extracted and the key technologies involved in each stage of situation generation are analyzed, including resource scheduling, detection and perception, data fusion, target recognition, threat assessment, situation analysis and product distribution. Finally, the future development direction of situation generation technology is discussed.
Abstract: The existing methods for parameters estimation of hybrid modulated signal combining linear frequency modulation and binary phase shift keying (LFM-BPSK) have low estimation accuracy in low signal-to-noise ratio (SNR) environments. In order to solve this problem, the Born-Jordan (BJD) time-frequency distribution of LFM-BPSK signal is derived in this paper, and the time-frequency characteristics of LFM-BPSK signal are analyzed, furthermore a parameter estimation algorithm based on the BJD time-frequency distribution is proposed. First, the initial frequency and frequency modulation slope of the LFM-BPSK signal are estimated using the Hough transform based on the BJD time-frequency transform, and the two-dimensional BJD time-frequency transform is converted into a one-dimensional time-domain signal, and the coder width is then calculated using the time-domain signal after dimension reduction. Then, in order to explore the theoretical lower bound of parameters estimation, the modified Cramer-Rao lower bound (MCRLB) for LFM-BPSK signal parameter estimation is also derived. Finally, three parameters are tested using Monte Carlo experiments. Simulation results show that the parameters estimation accuracy of the proposed algorithm is significantly better than existing algorithms at low SNR, and the performance is close to that of MCRLB.
Abstract: It is assumed in existing clutter sparse recovery space-time adaptive processing (STAP) that clutter training samples from different range cells satisfy the stationarity condition. However, there are many non-ideal factors in the actual systems, such as the internal clutter motion (ICM) , which will cause clutter model mismatch, resulting in inaccurate estimation of the clutter-plus-noise covariance matrix (CCM), and then the performance of STAP algorithm will be greatly reduced. In this paper, a variational Bayesian inference STAP algorithm for non-stationary clutter suppression is proposed to address the problem of non-stationary clutter suppression under ICM. First, a non-stationary clutter model is used to model the non-stationarity among the clutter training samples. Then, the variational Bayesian inference method is introduced to perform sparse recovery of the clutter space-time power spectrum. Finally, the CCM is estimated to achieve effective suppression of non-stationary clutter. Simulation experiments show that the proposed method is better than the existing sparse Bayesian learning STAP method in the case of non-stationary clutter environment with ICM.
Abstract: In order to solve the problem of which complex network is more effective for multifunction radar signal sorting, an improved limited penetrable visual graph (ILPVG) algorithm is proposed, and different complex network building algorithms are used to analyze the network model according to the topological attributes and centrality indicators of the complex network. Then, the radar signal sorting results are obtained by detecting the community structure through label propagation algorithm and density peak clustering algorithm. Simulation results show that the complex networks based on ILPVG algorithm and limited penetrable visual graph (LPVG) algorithm are higher than other networks in terms of network connectivity and compactness in the multifunction radar sorting scenario. The sub-community results and radar sorting accuracy obtained by the ILPVG network through the label propagation algorithm are higher than those of other networks, and the radar signal sorting accuracy is 3. 46% higher than that of LPVG, and significantly better than those of sorting methods based on the k-means and density-based spatial clustering of applications with noise algorithm, which indicates the effectiveness and superiority of the ILPVG algorithm in radar signal sorting.
Abstract: Due to the presences of a large number of buildings in ports and other areas, the navigation radar signals detected by specific emitter identification devices are affected by serious multi-path effects. In order to solve the above problems, a radar reference clock cycle feature extraction method is proposed in this paper, and based on this feature, the specific emitter identification of navigation radar is conducted in a harsh propagation environment. For the four quantum range working modes of two S-band navigation radars, the validity of radar repetition interval signature extraction is verified, and a linear classification model is constructed to verify the recognition validity, which verifies the effectiveness of the specific emitter identification method based on the base clock cycle feature against harsh propagation environment.
Abstract: A multi-level multifunctional radar behavior level representation model is established to address the problems of complex and varied styles, incomplete overall feature representation, and insufficient ability to provide key information in signal level analysis of multifunctional radar. A fusion network structure based on parallel processing of one-dimensional deep convolution neural network and gated recurrent unit is proposed. On the basis of using multi-level models to clearly and effectively characterize and analyze the behavior of multifunctional radar, combined with the advantages of two networks in local depth feature extraction and global time-series feature extraction, the behavior identification of typical functions of multifunctional radar has been achieved. The simulation experiment results show that, with a high degree of parameter interleaving, the network achieves a behavior recognition accuracy of 95. 6% for the four typical functions of multifunctional radar, which proves that the proposed parallel network algorithm has good application prospects in the field of reconnaissance intelligence analysis.
Abstract: A method for human target detection is proposed based on 77 GHz frequency modulated continuous wave radar, which utilizes the multipath effect of electromagnetic waves in non-line of sight environments. First, a multipath propagation model is established, and an effective method for generating two-dimensional coordinate point clouds is proposed through in-depth analysis of the model. In order to improve the accuracy of direction of arrival measurement and meet real-time requirements, an improved method based on minimum variance distortionless response is proposed to estimate the direction of arrival of the target. This method significantly reduces the computational complexity through iterative inverse operations. Then, in order to suppress excess stationary clutter, the clutter suppression method of principal component analysis is introduced. By performing principal component analysis on the echo data, the first principal component is filtered out and the data is reconstructed to achieve the effect of clutter suppression. Finally, the experimental results indicate that the proposed method can accurately detect targets outside the radar line of sight. This research provides new ideas and technical support for future radar technology applications, especially in fields such as safety monitoring and autonomous driving.
Abstract: Phased array radar adjusts the beam direction by electrical scanning, and completes the target angle measurement by measuring the deviation between the target echo and the expected beam pointing. When the actual beam pointing deviates from the expected, there will be errors in the target angle calculation. With the increasing demand for radar angle measurement accuracy, the influence of beam pointing deviation on radar angle measurement performance will become a key factor. Beam pointing deviation can usually be calibrated and compensated in the microwave anechoic chamber. However, modern large-scale phased arrays make beam pointing calibration difficult and even impractical in anechoic chambers due to their large scale. In this paper, a field high accuracy calibration method of radar beam pointing deviation is proposed for phased array radar based on inertial navigation to achieve array attitude measurement. First, the main reasons for the beam pointing deviation of phased array radar are analyzed, which are related to inertial navigation installation error, electrical axis and mechanical axis pointing deviation, and beam control code calculation error. Then, an error propagation model is established. A calibration method is presented to solve the beam pointing deviation and compensate it by measuring error data of radar tracking calibration. Finally, the field experiment verification is completed. The experimental results show that the beam pointing deviation can be greatly reduced by using the proposed method for field calibration, which has great reference value for the engineering implementation of high accuracy angle measurement for large scale phased array radar.
Abstract: A forward simulation model for spaceborne millimeter wave radar consisting of 9 sub modules is constructed in this paper. Weather research and forecasting simulation of cloud scenarios and random data simulated by this forward model are used for the sensitivity analysis of payload and platform parameters which is carried out to illustrate the influence of payload and platform parameter settings on the detection performance of the spaceborne millimeter wave radar. Analysis shows that the detection performance of the spaceborne millimeter wave radar with the configuration of antenna diameter of 2. 5 m and orbital altitude of 400 km~ 450 km is more than 7 times higher than CloudSat cloud profile radar; the impact of noise on the extraction of reflectivity factor can be effectively reduced when the signal-to-noise ratio reaches 25 dB; the detection accuracy of reflectivity factor within ±1 dB can be met when the radar calibration constant error is within 3. 36%; for a spaceborne millimeter wave radar platform with an orbital altitude of 400 km, the two sub-satellite observation areas before and after are completely misaligned when the attitude angle changes by more than 0. 13 °, meanwhile the positions of the two sub-satellite points before and after differ by 5 km when the attitude angle changes by more than 0. 75 °.
Abstract: In response to the problems of inefficient design process, incomplete optimization schemes, and non-intuitive optimization results in the traditional structural optimization design of the Stewart platform, based on deep analysis of the kinematic characteristics of the Stewart platform, the kinematic equations of the platform are established, and the reachable workspace and flexible workspace of the platform are obtained through simulation technology. The multi-objective ant lion (MOALO) algorithm is applied to the structural optimization design of the Stewart platform, and with the Jacobian matrix condition number and available operability as optimization objectives, multiple sets of optimization solutions, namely Pareto optimization solution sets, are obtained through simulation software. Taking the Stewart platform used as a motion simulator as an example for specific optimization design analysis, the effectiveness and feasibility of the algorithm are verified by solving the volume ratio of flexible workspace. In the structural optimization design of the Stewart platform, the MOALO algorithm has better convergence and coverage in multi-objective optimization problems compared to evolutionary genetic algorithm, multi-objective particle swarm optimization algorithm, etc. , and it is more in line with practical multi-objective optimization engineering design.
Abstract: In order to improve the isolation effect and stability accuracy of shipborne two-dimensional stable platform, the control effects of speed feedforward proportional-integral (PI) controller and linear active disturbance rejection controller are compared. First, on the basis of the mathematical model of two-dimensional stable platform servo system, PI controller and linear active disturbance rejection controller based on ship rocking speed feedforward are designed, and simulation model is established in the simulation software. Then, using actual ship rocking motion data as the excitation input control model, the stability accuracy of the pitch frame of conventional PI control, speed feedforward PI control, and linear active disturbance rejection control is analyzed. Simulation results show that the stability accuracy of linear active disturbance rejection control is significantly better than that of speed feedforward PI control. Finally, it is verified through offshore experiments that the two-dimensional stable platform based on linear active disturbance rejection control has high stability accuracy and can meet the engineering application and performance requirements of the stable platform servo system.
Abstract: In order to meet the demand for omnidirectional high gain antennas in base stations and wireless local area network applications, a design of an integrated printed dipole antenna based on lumped Balun structure is proposed. Firstly, a lumped Balun structure is designed according to the principle of a 3 dB bridge circuit, and the performance of the lumped Balun structure is verified by simulation software. The lumped Balun is composed of microstrip lines and lumped elements. After the input signal enters the Balun, signals with equal amplitude and 180° phase difference can be output from two output ports. Then, according to the principle of maximum transmission and minimum reflection, the dipole antenna is designed, and the lumped Balun is integrated with the dipole antennas printed on both sides of the dielectric substrate to complete the design of the Balun integrated dipole antenna. Finally, the optimal structure of the antenna is determined through electromagnetic simulation calculation and optimization, and prototype fabrication and measurement are carried out. The measured results show that the antenna can achieve horizontal omnidirectional high-gain radiation in the bandwidth range of 1. 35 GHz~ 1. 45 GHz. This antenna has the characteristics of light weight, low profile, and easy tuning, which provides a novel antenna structure for communication, broadcasting, and military system terminal antenna arrays.
Abstract: An octave L-band pyramid horn feed source based on metamaterials is studied. The horn feed with excellent radiation characteristics is obtained due to metamaterial structure onto the inner wall of pyramid horn. A metal ‘cross line’ shaped metamaterial unit is designed and optimized, which has a three-dimensional structure with an orthogonal metal rectangular prism at the top, connected to the inner wall of the horn through the metal rectangular prism at the center, and periodically arranged to form an impedance metasurface. Metamaterial structure exhibits different wave impedances in TE and TM modes, which can achieve balanced mixing of propagation modes within the horn under specific conditions, thereby achieving beam equalization and low cross polarization. Simulation results show that between 1. 35 GHz and 2. 70 GHz, the standing wave ratio of the feed source is less than 1. 25, the illumination angle is 20 °, and the cross polarization is less than -18 dB. Calculated using a standard Coriolis antenna, the efficiency is over 60%, and the sidelobes are below -16 dB. Compared with commonly used corrugated horn and smoothed horn in engineering, the electrical performance of the designed metamaterial horn is comparable. However, in terms of processing difficulty, production cost, and volume weight, the designed metamaterial horn has significant advantages.
Abstract: Taking advantage of high peak power and high efficiency of vacuum tube, the high-power transmitting module based on X band traveling wave tube is studied. The key technologies such as the design of 8-channel transmitting module, miniaturized packaging of high-voltage module and amplitude phase consistency control are introduced in this paper and an 8-channel traveling wave tube transmitting module is developed based on these technologies. The module adopts an integrated design method that uses a set of power supply to simultaneously power 8 tubes, which improves the power density of the module, reduces the volume of the transmitting component, and meets the requirements of the radar array. By adjusting the amplitude and phase consistency of each channel of the transmitting module, an 8-channel power combining test is conducted. The test data achieves the expected results and the feasibility of the proposed technology is further verified. The module is a new type of traveling wave tube amplifier transmitting module, which has a small size, high power density and relatively low price, and provides a new solution for phased array radar transmitting unit.
Abstract: A high-performance broadband medium-power amplifier chip is designed and implemented in this paper. The chip adopts the 0. 25 μm GaAs pseudomorphic high electron mobility transistor process and utilizes a cascode circuit configuration, which significantly improves the gain level of the amplifier. Additionally, the introduction of negative feedback technology effectively improves the flatness of the gain and greatly expands the operating bandwidth range of the amplifier, enabling it to cover a wide frequency range from 6 GHz to 18 GHz, meeting the diverse needs of wireless communication and radar systems. Experimental results show that the chip achieves a stable gain of 17 ± 0. 3 dB within the specified frequency band, with both input and output return losses better than -10 dB, demonstrating excellent matching performance. At a working voltage of 5 V, the current consumption is only 63 mA, and the 1 dB compression point output power is as high as 15 dBm, ensuring stability and reliability at high-power output. The compact chip design, with an area of only 1. 94 mm × 1. 08 mm, provides significant convenience for system integration.
Abstract: The warning of unsafe behavior inside the vehicle is an important means to reduce traffic accidents. However, existing research mainly focuses on detecting dangerous behaviors of drivers, while dangerous behaviors of passengers are often overlooked. Therefore, an algorithm for analyzing dangerous behaviors of both drivers and passengers based on vehicle-cloud computing collaboration is proposed in this paper. First, the driver and passengers are distinguished using a detection and personnel identity analysis model based on coarse-grained depth estimation. Then, a detection model based on ByteTrack multi-object tracking is used to detect whether passengers are out of their seats, and a multi-task joint model for head pose estimation and fatigue state detection is employed to detect dangerous driving behaviors of the driver. Finally, video clips of dangerous behaviors are uploaded to the cloud for verification. Experimental results show that the proposed detection model based on coarse-grained depth estimation and the personnel identity analysis model increase F1-Score by 5. 1% compared to the region of interest method, the head pose estimation branch of the multi-task joint model increases F1-Score by 5. 2% compared to the LwPoser model, the fatigue detection branch increases the mean average precision by 2. 4% compared to the YOLOv6s model, and the use of high-precision cloud-based models increases F1-Score by 7. 6% during verification. The above results demonstrate the effectiveness of the proposed algorithm.
Abstract: Wafer level packaging (WLP) technology can significantly compress the volume and weight of the front-end transceiver module, realizing the miniaturization of active phased array radar. However, it also brings great challenges, such as heat management, channel isolation, signal cross-talk and adaptability of repairing and testing. Due to the introduction of more process steps and complex package architecture, how to test wafer level packaging modules to ensure yield and reduce testing costs has become an important technical issue. In this paper, the wafer level heterogeneous integration technology in millimeter-wave is summarized. Besides, the testing requirements and technical challenges, along with some integration solutions and testing process of typical products are deeply discussed. The existing key technologies are sorted out from three aspects: wafer level testing with probe station, socket testing and over the air (OTA) testing. It can provide some valuable references for the construction of radio frequency wafer level 3D packaging modules.
Abstract: According to the basic theory of electromagnetic vortex wave, the properties of electromagnetic vortex waves are simulated and analyzed. Based on the uniform circular array model, the aliasing characteristics of the square Bessel function at the pitch Angle are verified. The principles and properties of linear Doppler, rotary Doppler and micro-Doppler are compared to show the advantages and disadvantages of vortex detection. The research progress of electromagnetic vortex wave Doppler detection in recent years is summarized, and the detection ability is verified by simulation. At the same time, the key problems in rotary Doppler and micro-Doppler detection are summarized, and the direction of further research is pointed out.
Abstract: Feature detection is an effective way to improve the detection of small sea-surface targets. Aiming at the problems of low detection probability of low-dimensional features and difficult control of high-dimensional feature false alarms, a high-dimensional feature detection method based on random forest with controllable false alarms is proposed in this paper. First, multi-dimensional features are extracted from multiple domains of time domain, frequency domain, and time-frequency domain. The detection problem is converted into a two-class classification problem in high-dimensional feature space. Second, two types of balanced training samples including sea clutter and target echo are obtained by simulating returns with target. Third, random forest algorithm is introduced into high-dimensional feature space, and function expression of the splitting factor and the false alarm rate is established to obtain the control region of false alarm. Finally, it is verified by the IPIX measured data that the proposed detector has a certain performance improvement and meets the requirements of real radar with constant false alarm detection.
Abstract: Jamming is one of the most important challenges airborne radar faces in the battle use, and so the anti-jamming capability becomes a key parameter used to evaluate the performance of airborne radar. First, the jamming environment that airborne radar encounters is introduced in this paper, then anti-jamming mind and advantages of anti-jamming strategy based on jamming environment are described. Further principles and implementations of some frequently-used anti-jamming methods are presented. Specially, recently focused anti-jamming techniques with polarimetry and with multistatic radar collaboration aimed at main-lobe jamming suppression are detailed. Finally, due to the progress of the jamming technique, future development tendency on the anti-jamming technique is analyzed.
Abstract: The cognitive radar architecture contributes to enhancing the intelligence of radar anti-jamming technology. Addressing the issue of radar perception of electromagnetic interference in the field of cognitive anti-jamming technology, a multi-node jamming modulation type recognition method based on deep learning is proposed. This method targets various nodes in radar signal processing, such as digital beamforming, adaptive sidelobe cancellation, before and after pulse compression, and post-moving target detection. The time-frequency plane and range-Doppler plane of multiple nodes are used as joint feature extraction objects for jamming signals. A deep learning-based multi-node jamming recognition strategy model is established to improve jamming recognition accuracy in various scenarios. To enhance the extraction capability of jamming features and the training efficiency of the network, the deep learning algorithm for jamming recognition incorporates attention mechanisms and residual networks into the convolutional neural network. This establishes an interference type recognition network structure for multi-node strategies, achieving recognition of various jamming types in different scenarios. Simulation results show that in a single jamming scenario, the proposed algorithm achieves a jamming recognition accuracy of up to 92?? at a jamming-to-noise ratio (JNR) of 14 dB. In multiple jamming scenarios, the proposed algorithm, supported by different node strategies, achieves an accuracy of up to 90%.
Abstract: The mainlobe deceptive jamming has the same angle as the real target scene, and the two are highly similar in multiple domains, which seriously reducing the detection and judgment capabilities of the synthetic aperture radar system for real targets. To address this issue and ensure effective suppression of mainlobe deceptive jamming, a real-time and fast processing anti-mainlobe deceptive jamming algorithm is proposed in this paper. First, an echo recovery framework based on azimuth phase coding is proposed and the framework can group the raw echo data. Secondly, a fast algorithm for modular processing is proposed to speed up the processing efficiency of the proposed method. Finally, the effectiveness and feasibility performance of the proposed method are verified through point target and distributed targets simulation experiments. By comparing with the traditional mainlobe deceptive jamming method, the proposed method can not only reduce the computational complexity, but also reduce the occupation of system resources.
Abstract: Firstly, the key parameters of each subsystem in the radar system are introduced and the constraints between the parameters as the constraint condition for radar optimization are analyzed. Secondly, the advantages and disadvantages of current typical multi-objective optimization algorithms are compared and their different application fields are analyzed. Thirdly, the intelligent optimization technologies that have been applied to radar design are classified and introduced from different perspectives of radar waveform design, antenna design, transmitter and so on. Finally, the future development trend of the intelligentization of radar is prospected. It is hoped that the summary analysis of this article can provide a reference for the intelligent design of radar in the future.
Abstract: With the development and performance improvement of anti-jamming technology for anti-ship missile, the traditional on-platform shipboard jamming technology has not been sufficient to fully resist various naval war threats, therefore as an off-platform jamming method with networking capabilities, outboard active decoy has attracted much attention from navies of various countries. Firstly, the jamming mechanism and working characteristics of outboard active decoy are introduced, and the jamming strategy of using outboard active decoys in the ship defense system is analyzed in this paper, and the effectiveness of outboard active decoy is demonstrated too. Then, on this basis, the developments and technical characteristics of foreign outboard active decoy equipment are clarified. Finally, the countermeasures that can be adopted are analyzed for the anti-outboard interference measures of the new anti-ship missile seeker. The research content gives a comprehensive introduction for the outboard active decoy and its countermeasures, which can provide support for the subsequent design of outboard jamming products and anti-jamming technology of seeker.
Abstract: In military and civilian fields such as electronic warfare and wireless network security, specific emitter identification (SEI) has extremely high application value. The traditional methods are mainly based on manual feature extraction, which rely on prior knowledge and have poor generalization. Deep learning methods mostly use images containing two-dimensional information as input, which is easy to miss key information. In order to solve the above problems, a solution method using the afterglow map of the digital spectrum as the input of the deep learning model is proposed, so as to realize the SEI task. Firstly, an emitter signal detection and data acquisition system are built to obtain the afterglow map of the digital spectrum for the Wi-Fi emitter signal, and the first SEI dataset based on the afterglow map of the digital spectrum is established. Secondly, the problem of signal recognition is transformed into the problem of target detection by using the feature that the image contains more information. Finally, experimental verification is performed on the Wi-Fi emitter identification dataset (WFEID). Experimental results show that the P, R, F1 and mAP of YOLOv5s can reach more than 87. 5% on WFEID, which proves the effectiveness of the method using the afterglow map of the digital spectrum as the input of deep learning model in tasks of specific emitter identification.
Abstract: Radar has to deal with complex and changeable jamming scenarios in the process of work, and it is difficult to exhaust anti-jamming approaches. In the face of these confrontation scenarios, the artificial anti- jamming flow and suppression strategy cannot be guaranteed due to the limited experience and knowledge of experts. Based on the application requirements of radar antijamming, this paper introduces reinforcement learning method and proposes an intelligent anti-jamming method based on reinforcement learning model. Two typical reinforcement learning algorithms, Q-learning and Sarsa, are respectively used to calculate and iterate the value function in the anti-interference model, so that the anti-interference strategy has the function of self-updating and optimization. Simulation results show that the reinforcement learning algorithm can converge and optimize the anti-jamming strategy. Compared with the traditional anti-jamming design method, the intelligence of radar anti-jamming is improved effectively.
Abstract: Collaborative R&D platform on which processes,tools,data and knowledge were integrated was built through analyzing radar R&D problems.Unified design environment,unified process system,unified data space that composed radar R&D system were described.Three-tier structure of radar R&D platform was present.Management platform on collaborative tier provides the ability of task transition across organization and discipline.Design platform on application tier integrates knowledge and tool.Data platform on data tie...
Abstract: Based on the pulse load characteristics of the transmitting unit, the equivalent circuit and the mathematical model of the transmitting unit are established. Four states of the transmitting unit power supply system are studied by the state space segmentation method. Based on the system states equations, the theoretical calculation formula of the voltage drop with the transmitting unit is derived. The main factors of the voltage drop are also obtained. In order to satisfy the constraint of the voltage drop, the accurate and approximate formulas of the capacitance for energy storage are derived. The achievements are verified by the simulation. The proposed propositions and inferences constitute the basic theory of the power supply system design of the transmitting unit. The conclusions lay a theoretical foundation for the design of power supply system of phased array radar with long pulse width, which has great engineering application value.
Abstract: The anti-jamming ability of radar is directly associated with winning or not in war. Combined with the developing direction of electronic war and the existing problem of anti-jamming in radar system, the demand in anti-jamming design of modern radar system is analysed. Firstly, based on the anti-jamming source reconnaissance and analysis, as well as the targets detection and track and adaptive anti-jamming, and self-jamming indexes which are used to assess the fighting ability of radar is constructed. Secondly, the demand of anti-jamming design is proposed in self-adaption closed-loop, integrated compatibility and big data accumulation. Lastly, the particle design is required by comparing multiple testing results in out-field.
Abstract: In computational electromagnetic field,the moment method based on surface integral equations for analysis of electromagnetic scattering by 3-D homogenous dielectric and PEC objects is a hot topic all through.In this paper,the EFIE integral equation is built on the surface and PMCHW integral equations is constructed based on the surface of homogenous dielectric object.Combined with adaptively modified characteristic basis function method(AMCBFM) that is based on dividing the object geometry into distinct blo...
Abstract: The sorties determination principle is discussed for narrowband coherent radar targets with non-rigid-structure based on a long coherent integration time in this paper.Firstly a novel signal model is proposed and some new concepts are put forward,such as common rotation Doppler,radial Doppler,chirp Doppler.And then it is pointed out that the initial frequency of target time-frequency distribution is decided by the sum of common rotation Doppler and radial Doppler,the trend is decided by chirp Doppler.Accord...
Abstract: To meet the requirement of the deep space exploration of China, the planet radar equipment development is suggested to enhance the deep space exploration system based on its recent working mode. The ground-based deep space expoloration network of USA adopts deep space telemetry, track and command network, very long baseline array network and ground-based planet radar. By calling different equipments, different working modes can be formed, and all equipemnts are used with high efficiency. Modes of deep space exploration of USA are investigated and constituting programming of ground-based planet radar and research of key techniques are suggested. The purpose is to provide support and reference for China's deep space exploration in the future.
Abstract: The detection of sea surface unmanned aerial vehicles (UAVs) belongs to the problem of small target detection in the background of sea clutter due to weak echoes, and joint multi-feature detection is an effective way to solve such problems. Aiming at the existing time-frequency (TF) tri-feature detection method, which has too much computational complexity in the feature extraction stage and is difficult to realize real-time detection, this paper proposes a fast TF-map-based multi-feature detection method for sea surface UAVs. First, the segmented FFT is performed on the radar complex echo data, and the computed Doppler amplitude spectrum is aligned and spliced along the Doppler dimension so as to construct a fast time-frequency map. Second, the fast TF map is normalized to achieve clutter suppression and enhancement of the target echoes, and three kinds of time-frequency features are extracted based on the normalized fast TF map. Third, the fast convex hull learning algorithm is utilized to train the decision judgement region under the given false alarm probability. Finally, the effectiveness of the proposed method is validated and analyzed by the measured UAV data.
Abstract: Pulse Doppler radar generally needs to process and detect multiple sets of different pulse repetition frequency (PRF) pulse groups. Different from the multi-frequency variation mode, this paper studies the method of multi-group PRF coherent integration. PRF of different frequencies is processed as a group, so that the echoes of each PRF pulse group can be coherently accumulated, and only one frame of data needs to be detected, which improved poor detection performance of the traditional method due to separate detection. The influence of each parameter on the detection result is analyzed and the main side-lobe ratio of the processing result is used as the fitness evaluation value. The genetic algorithm is used to quickly search for the required parameter combination and reduce the number of searches. The simulation example shows that the proposed method can efficiently obtain the parameter combination with excellent performance by genetic algorithm, the detection performance is effectively improved and the requirement of signal-to-noise ratio for successful ambiguity resolution is greatly reduced.
Abstract: The rotation-induced micro-Doppler effect is common in radar detection scenarios, and the resulting micro-motion features are related to the geometric and kinematic parameters of the target. This paper comprehensively analyzes the formation mechanism of rotating blades micro-motion echo time-frequency features based on half-wave cancellation from the line integral model of micro-motion echo. Firstly, the formation mechanism of the instantaneous frequency of rotating micro-motion is analyzed under the far-field condition based on half-wave cancellation, which explains the double-end effect of the time-frequency characteristics of rotating micro-motion. Further, the half-wave cancellation analysis is extended to the near-field condition, and the effect of the double-ended region and the specular scattering region of the time-frequency diagram accentuated under near-field conditions is explained. Moreover, for both far-field and near-field conditions, this paper gives a quantitative analytical calculation method for the time-frequency results. This paper analyzes the time-frequency features of near-field and far-field from the perspectives of image shape and energy change, discusses the effects of different conditions and parameters on the shape and details of the time-frequency features, and unifies the near-field and far-field analyses based on the half-wave cancellation analysis, meanwhile, the line integral model and the local scattering model are linked. The simulation experiments verify the correctness of the proposed analytical methods.
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