Characterization and Application of S-Band Polarimetric Radar and X-Band Phased Array Radar for a Tornadic Storm Event on June 16,2022

The X-band phased array radar offers faster scanning speed and higher spatial resolution compared to the S-band radar,making it capable of enhancing tornado monitoring and early warning capabilities.This study analyzed the characteristics and nowcasting signals of a tornado case that occurred on June 16,2022 in the Guangzhou region.Our findings indicate that the violent contraction of rotation radius and the dramatic increase in rotation speed were important signal characteristics associated with tornado formation.The X-band phased array radar,with its high temporal and spatial resolution,provided an opportunity to capture early warning signals from polarimetric characteristics.The X-band phased array radar demonstrated noteworthy ability to identify apparent tornado vortex signature(TVS)features in a 10-minute lead time,surpassing the capabilities of the CINRAD/SA radar.Additionally,due to its higher scanning frequency,the Xband phased-array radar was capable of consistently identifying TVS with shorter intervals,enabling a more precise tracking of the tornado's path.The application of professional radars,in this case,provides valuable insights for the monitoring of evolutions of severe local storms and even tornadoes and the issuance of early warning signals.

Quantitative Precipitation Estimation Using X-band Phased Array Weather Radar

This study utilized data from an X-band phased array weather radar and ground-based rain gauge observations to conduct a quantitative precipitation estimation(QPE)analysis of a heavy rainfall event in Xiong an New Area from 20:00 on August 21 to 07:00 on August 22,2022.The analysis applied the Z-R relationship method for radar-based precipitation estimation and evaluated the QPE algorithm s performance using scatter density plots and binary classification scores.The results indicated that the QPE algorithm accurately estimates light to moderate rainfall but significantly underestimates heavy rainfall.The study identified disparities in the predictive accuracy of the QPE algorithm across various precipitation intensity ranges,offering essential insights for the further refinement of QPE techniques.

Dwell scheduling algorithm for multifunction phased array radars based on the scheduling gain

A real-time dwell scheduling model, which takes the time and energy constraints into account is founded from the viewpoint of scheduling gain. Scheduling design is turned into a nonlinear programming procedure. The real-time dwell scheduling algorithm based on the scheduling gain is presented with the help of two heuristic rules. The simulation results demonstrate that compared with the conventional adaptive scheduling method, the algorithm proposed not only increases the scheduling gain and the time utility but also decreases the task drop rate.

Novel cued search strategy based on information gain for phased array radar

A search strategy based on the maximal information gain principle is presented for the cued search of phased array radars. First, the method for the determination of the cued search region, arrangement of beam positions, and the calculation of the prior probability distribution of each beam position is discussed. And then, two search algorithms based on information gain are proposed using Shannon entropy and Kullback-Leibler entropy, respectively. With the proposed strategy, the information gain of each beam position is predicted before the radar detection, and the observation is made in the beam position with the maximal information gain. Compared with the conventional method of sequential search and confirm search, simulation results show that the proposed search strategy can distinctly improve the search performance and save radar time resources with the same given detection probability.

Variable scheduling interval task scheduling for phased array radar

A scheduling algorithm is presented aiming at the task scheduling problem in the phased array radar. Rather than assuming the scheduling interval(SI) time, which is the update interval of the radar invoking the scheduling algorithm, to be a fixed value,it is modeled as a fuzzy set to improve the scheduling flexibility.The scheduling algorithm exploits the fuzzy set model in order to intelligently adjust the SI time. The idle time in other SIs is provided for SIs which will be overload. Thereby more request tasks can be accommodated. The simulation results show that the proposed algorithm improves the successful scheduling ratio by 16%,the threat ratio of execution by 16% and the time utilization ratio by 15% compared with the highest task mode priority first(HPF)algorithm.

Design and Realization of Phased Array Radar Optical Fiber Transmission System

One optical fiber transmission system is designed. The modularization optical fiber transmission adapters were utilized in the system, so the system structure could be flexibly sealable. The sub-array adapter and signal processor adapter were designed and realized utilizing the new field programmable gate array （FP- GA） which could drive the optical transceiver. The transmission agreement was designed based on the data stream. In order to solve the signal synchronization problem of the optical fiber transmitted phased array radar, a method named synchronous clock was designed. The fiber transmission error code rate of the system was zero with an experimental transmission velocity of 800 Mbit/s. The phased array radar system has detected the airplane target, thus validated the feasibility of the design method.

Cued search algorithm with uncertain detection performance for phased array radars

A cued search algorithm with uncertain detection performance is proposed for phased array radars. Firstly, a target search model based on the information gain criterion is presented with known detection performance, and the statistical characteristic of the detection probability is calculated by using the fluctuant model of the target radar cross section （RCS）. Secondly, when the detection probability is completely unknown, its probability density function is modeled with a beta distribution, and its posterior probability distribution with the radar observation is derived based on the Bayesian theory. Finally simulation results show that the cued search algorithm with a known RCS fluctuant model can achieve the best performance, and the algorithm with the detection probability modeled as a beta distribution is better than that with a random selected detection probability because the model parameters can be updated by the radar observation to approach to the real value of the detection probability.

An adaptive dwell time scheduling model for phased array radar based on three-way decision

Real-time resource allocation is crucial for phased array radar to undertake multi-task with limited resources,such as the situation of multi-target tracking,in which targets need to be prioritized so that resources can be allocated accordingly and effectively.A three-way decision-based model is proposed for adaptive scheduling of phased radar dwell time.Using the model,the threat posed by a target is measured by an evaluation function,and therefore,a target is assigned to one of the three possible decision regions,i.e.,positive region,negative region,and boundary region.A different region has a various priority in terms of resource demand,and as such,a different radar resource allocation decision is applied to each region to satisfy different tracking accuracies of multi-target.In addition,the dwell time scheduling model can be further optimized by implementing a strategy for determining a proper threshold of three-way decision making to optimize the thresholds adaptively in real-time.The advantages and the performance of the proposed model have been verified by experimental simulations with comparison to the traditional twoway decision model and the three-way decision model without threshold optimization.The experiential results demonstrate that the performance of the proposed model has a certain advantage in detecting high threat targets.

Reliability of X-band Dual-polarization Phased Array Radars Through Comparison with an S-band Dual-polarization Doppler Radar

Based on the observations of a squall line on 11 May 2020 and stratiform precipitation on 6 June 2020 from two X-band dual-polarization phased array weather radars(DP-PAWRs)and an S-band dual-polarization Doppler weather radar(CINRAD/SA-D),the data reliability of DP-PAWR and its ability to detect the fine structures of mesoscale weather systems were assessed.After location matching,the observations of DP-PAWR and CINRAD/SA-D were compared in terms of reflectivity(Z_(H)),radial velocity(V),differential reflectivity(Z_(DR)),and specific differential phase(K_(DP)).The results showed that:(1)DP-PAWR has better ability to detect mesoscale weather systems than CINRAD/SAD;the multi-elevation-angles scanning of the RHI mode enables DP-PAWR to obtain a wider detection range in the vertical direction.(2)DP-PAWR’s Z_(H)and V structures are acceptable,while its sensitivity is worse than that of CINRAD/SA-D.The Z H suffers from attenuation and the Z_(H)area distribution is distorted around strong rainfall regions.(3)DP-PAWR’s Z_(DR)is close to a normal distribution but slightly smaller than that of CINRAD/SA-D.The K_(DP)products of DP-PAWR have much higher sensitivity,showing a better indication of precipitation.(4)DP-PAWR is capable of revealing a detailed and complete structure of the evolution of the whole storm and the characteristics of particle phase variations during the process of triggering and enhancement of a small cell in the front of a squall line,as well as the merging of the cell with the squall line,which cannot be observed by CINRAD/SA-D.With its fast volume scan feature and dual-polarization detection capability,DP-PAWR shows great potential in further understanding the development and evolution mechanisms of meso-γ-scale and microscale weather systems.

Multi-target range and velocity measurements of a digital phased array radar system

As the core of a digital phased array radar system,a radar signal processing environment is created to measure multitarget range and velocity information. The radar echo signal is achieved by superposing target echo, noise, clutter and jamming signals linearly. Considering that these signals have many types,two typical combinations are selected to construct the multi-target echo signal and the simulated echo signal is used as the input of the signal processing environment. This environment mainly adopts pulse compression,moving target indication and detection technologies to process the echo signal.It is found that the frequency domain method is more desirable for the pulse compression effect than the time domain method,and multi-target range information can be measured from the moving target indication result after using a double delay canceller. A new moving target detecting method is proposed,which can present the positive and negative velocity accurately with the multi-target range and velocity measured simultaneously. Simulation results indicate that the potential targets are detected from the chaotic radar echo signals successfully,and their range and velocity can be figured out correctly in the built radar signal processing environment.

Comparison of the Observation Capability of an X-band Phased-array Radar with an X-band Doppler Radar and S-band Operational Radar

An X-band phased-array meteorological radar （XPAR） was developed in China and will be installed in an airplane to observe precipitation systems for research purposes.In order to examine the observational capability of the XPAR and to test the operating mode and calibration before installation in the airplane,a mobile X-band Doppler radar （XDR） and XPAR were installed at the same site to observe convective precipitation events.Nearby S-band operational radar （SA） data were also collected to examine the reflectivity bias of XPAR.An algorithm for quantitative analysis of reflectivity and velocity differences and radar sensitivity of XPAR is presented.The reflectivity and velocity biases of XPAR are examined with SA and XDR.Reflectivity sensitivities,the horizontal and vertical structures of reflectivity by the three radars are compared and analyzed.The results indicated that while the XPRA with different operating modes can capture the main characteristic of 3D structures of precipitation,and the averaged reflectivity differences between XPAR and XDR,and XDR and SA,were 0.4 dB and 6.6 dB on 13 July and-4.5 dB and 5.1 dB on 2 August 2012,respectively.The minimum observed reflectivities at a range of 50 km for XPAR,XDR and SA were about 15.4 dBZ,13.5 dBZ and-3.5 dBZ,respectively.The bias of velocity between XPAR and XDR was negligible.This study provides a possible method for the quantitative comparison of the XPAR data,as well as the sensitivity of reflectivity,calibration,gain and bias introduced by pulse compression.

Research on Data Combination for Phased-Array Ground Penetrating Radar

To resolve the data combination of Phased-array Ground Penetrating Radar (PAGPR), we first build a model of PAGPR and a layered model, and then a new data combination algorithm is presented based on it. This method calculates time delay of multi-receivers, basing on the signal of the nearest receiver, then shifts other signals and adds them up, and gets one signal at last. It has been proved that this method can restrain noise, multiple waves, clutter waves and improve the precision of time location. In the end, an example is given to prove the method's efficiency.

Multiple-target tracking with adaptive sampling intervals for phased-array radar

A novel adaptive sampling interval algorithm for multitarget tracking is presented. This algorithm which is based on interacting multiple models incorporates the grey relational grade （GRG） into the particle swarm optimization （PSO）. Firstly, the desired tracking accuracy is set for each target. Secondly, sampling intervals are selected as particles, and then the advantage of the GRG is taken as the measurement function for resource management. Meanwhile, the fitness value of the PSO is used to measure the difference between desired tracking accuracy and estimated tracking accuracy. Finally, it is suggested that the radar should track the target whose prediction value of the next sampling interval is the smallest. Simulations show that the proposed method improves both the tracking accuracy and tracking efficiency of the phased-array radar.

An Optimal Sorting of Pulse Amplitude Sequence Based on the Phased Array Radar Beam Tasks

The study of phased array radar( PAR) pulse amplitude sequence characteristics is the key to understand the radar's working state and its beam's scanning manner.According to the principle of antenna pattern formation and the searching and tracking modes of beams,this paper analyzes the characteristics and differences of pulse amplitude sequence when the radar beams work in searching and tracking modes respectively.Then an optimal sorting model of pulse amplitude sequence is established based on least-squares and curve-fitting methods.This method is helpful for acquiring the current working state of the radar and recognizing its instantaneous beam pointing by sorting the pulse amplitude sequence without the necessity to estimate the antenna pattern.

Wigner Frequency Point Slice Analysis of Superposition Data for Phased-Array Ground Penetrating Radar

According to the frequency property of Phasedarray ground penetrating radar (PGPR), this paper gives a frequency point slice method based on Wigner time-frequency analysis. This method solves the problem of analysis for the PGPR's superposition data and makes detecting outcome simpler and detecting target more recognizable. At last, the analytical results of road test data of the Three Gorges prove the analytical method efficient. Key words phased-array ground penetrating radar - wigner time-frequency analysis - superposition data - object identification CLC number TN 715.7 Foundation item: Supported by the National Nature Science Foundation of China (50099620) and 863 Program Foundation of China (2001AA132050-03)Biography: ZOU Lian (1975-), male, Ph. D candidate, research direction: signal processing.

Computer Control Techniques of Phased Array Radars

The computer control techniques applicable to electronically scanned multifunction radars are presented. The software and hardware architecture for the real time control and the data processing within a phased array radar are described. The software system comprising a number of tasks is written in C language and implemented. The results show that the algorithm for the multitask adaptive scheduling and the multitarget data processing is suitable for multifunction phased array radars.

ALGORITHMS FOR TRACKING MANEUVERING TARGET WITH PHASED ARRAY RADAR

Several typical algorithms for tracking maneuvering target with phased array radar are studied in this paper. The constant gain filter with multiple models is analyzed. A typical method for adaptively controlling the sampling interval is modified. The performance of the single model and multiple model estimator with uniform and variable sampling interval are evaluated and compared. It is shown by the simulation results that it is necessary to apply the adaptive sampling policy based on the multiple model method when the maneuvering targets are tracked by the phased array radar since saving radar resources is more important. The adaptive algorithms of variable sampling interval are better than the algorithms of variable model. The adaptive policy to determine the sampling interval based on multiple model are superior than those based on the single model filter, because IMM estimator can adapt to the maneuver more quickly and the prediction covariance of IMM is the more sensitive and more reliable index than residual to determine the sampling interval. With IMM based method, lower sampling interval is required for a certain accuracy.

ADAPTIVE UPDATE RATE FOR PHASED ARRAY RADAR BASED ON IMMK-PF

Interacting Multiple Model Kalman-Particle Filter (IMMK-PF) has the advantages of particle filter and Kalman filter and good computation efficiency compared with Interacting Multiple Model Particle Filter (IMMPF). Based on IMMK-PF, an adaptive sampling target tracking algorithm for Phased Array Radar (PAR) is proposed. This algorithm first predicts Posterior Cramer-Rao Bound Matrix (PCRBM) of the target state, then updates the sample interval in accordance with change of the target dynamics by comparing the trace of the predicted PCRBM with a certain threshold. Simulation results demonstrate that this algorithm could solve the nonlinear motion and the nonlinear relationship between radar measurement and target motion state and decrease computation load.

PHASE AUTOFOCUSING ALGORITHM FOR COMPRESSED INVERSE SYNTHETIC APERTURE RADAR IMAGING

As same as the conventional inverse synthetic aperture radar（ISAR）, the compressed ISAR also requires the echo signal based motion compensation, which consists of the range alignment and the phase autofoeusing. A phase autofocusing algorithm for compressed ISAR imaging is presented. In the algorithm, phase autofocusing for the sparse ISAR echoes is accomplished using the eigenvector method. Experimental results validate the effectiveness of the algorithm.

Phased-MIMO雷达恒模正交波形优化设计

由于受到发射机功率和波形能量的限制,现代雷达系统一般选择恒模波形来实现发射功率的最大化利用。针对Phased-MIMO雷达子阵单元之间的恒模正交波形优化设计问题,基于矩阵谱逼近的思想,本文提出了一种新的波形设计框架。首先假设输出信干比的需求得到划分的子阵数目,根据最大信噪比准则对子阵单元进行波束形成,提高了雷达系统的抗干扰性能,其次采用迭代矩阵谱逼近算法(iterative matrix spectral approximation algorithm,IMSAA)对子阵单元之间的正交波形进行优化设计,相对于multi-CAN算法,该算法能够获得更好的相关性能,而且运算效率较高,最终实现了恒模波形的优化设计。仿真结果证明了算法的有效性。