Search

提出了一种基于Alpha stable分布的新型变异方法。针对粒子群算法容易陷入局部最优的缺点, 通过对比分析确定了一种调整Alpha stable分布的稳态系数动态变异策略, 使粒子群算法能够在搜索初始阶段具有更强的种群多样性以及算法探索能力, 减少陷入局部最优的可能; 在算法末期增强粒子群优化算法的局部搜索能力, 提高解的精度。将基于Alpha stable变异的粒子群优化算法(Alpha stable particle swarm optimization, ASPSO)与多种改进型粒子群优化算法以及差分进化算法(differential evolution algorithm, DE)进行了比较, 基准测试函数结果表明新建立的ASPSO算法极大地提高了算法的收敛速度和精度。将其应用到RAE2822翼型的单点跨声速减阻优化中, 在保持种群规模等参数相同的情形下, ASPSO算法的优化效果和效率都远高于传统PSO算法, 最终得到的翼型也比PSO优化的翼型具有更高的升阻比, 翼面波阻有明显降低。

Finding codes for the desired autocorrelation function (ACF) based on phase-coded modulation waveforms has always been a popular research topic, and the relevant literature is abundant. However, the optimized ACF may not be obtained in band-limited hardware due to the extended spectral sidelobes generated by instantaneous phase changes. Polyphase-coded FM (PCFM) waveforms based on continuous phase modulation (CPM), which uses a shape filter to smooth phase jumps, can provide effective spectral containment. However, for PCFM waveforms using the existing optimized phase codes, the original desired property of the ACF, e.g., a low integrated sidelobe level (ISL) or weighted ISL (WISL), will not be obtained because of the smoothness among all phases. Hence, PCFM waveforms based on CPM should be redesigned and optimized. Moreover, designing pulse-agile waveforms with different phase codes to mitigate range ambiguity has also attracted increased attention in recent years. However, different waveforms will yield range sidelobe modulation (RSM) in Doppler processing, which degrades the attendant Doppler coherency, leading to high sidelobes in the Doppler dimension. In this article, optimization algorithms for designing diverse PCFM waveforms and relevant joint mismatched filters (JMMFs) are proposed. A CPM-based cyclic algorithm (CPM-CA) using the method of alternating projection for optimizing the PCFM waveform with a desired ACF is proposed in the first step. The design of multiple diverse PCFM waveforms with similar ACFs and a small RSM effect is also considered. Then, to further optimize the ISL/WISL and reduce the RSM effect, a novel method for designing JMMFs using a cyclic algorithm (JMMF-CA) is proposed. Simulations and an experiment based on a real radar system indicate that the optimized PCFM waveforms and JMMFs using CPM-CA and JMMF-CA can yield a desired ISL/WISL while achieving a small RSM effect with a low loss of signal-to-noise ratio and satisfactory Doppler robustness.

Synthetic wideband signals can obtain a wide spectrum and thus achieve a high range resolution by synthesizing separately emitted signals. A synthetic wideband range profiling method for moving targets based on phase‐derived velocity measurement is proposed. Highly accurate velocity measurement results are obtained by analysing the echo phase information of a moving target, and the accuracy of the velocity estimation results can meet the requirement of the velocity compensation in the synthetic wideband range profiling process. After analysis of the spectrum envelope and the phase of a moving target, a method for synthesizing wideband signals in the frequency domain, thus obtaining a high‐resolution range profile, is developed. The constraint conditions for the motion compensation and synthesis process are analysed and discussed by simulation, and the effectiveness of the proposed method is verified under various circumstances.

In this article, we propose a phase-derived velocity measurement (PDVM) method for high-speed spatial targets based on the stepped-frequency chirp signal (SFCS). This method is capable of accurately measuring the velocity of high-speed targets and yields root-mean-squared error values at the level of centimeters per second; therefore, it has great potential for measuring the micromotion of targets and is of significant importance for target recognition. The traditional phase-derived measurement method is not applicable for high-speed targets. The main challenge that we have solved is how to extract the echo phase from the high-resolution range profile, which is corrupted by range migration, intrapulse motion, and range straddling under high-speed target conditions. To guide the implementation of the proposed method in radar systems, constraint conditions for the compensation accuracy are thoroughly derived and systematically justified under different radar parameter settings. The simulation results are presented to validate the high accuracy of the method under various circumstances. In addition, the small-amplitude micromotion measurement capability of the proposed method is verified, and reconstruction of the target micromotion trajectory is demonstrated.

Waveform diversity, which can be used to obtain synthetic bandwidth or mitigate range ambiguity, interference, and folded clutters, has attracted a great deal of attention in recent years. However, the range sidelobe modulation effect between agile pulses yields high range-Doppler sidelobes in pulse-Doppler (PD) radar applications, because of which traditional window functions or mismatched filters (MMFs) do not apply. In this article, a Doppler-tuned matched filter is used to equivalently obtain the PD result. Then, to mitigate the high range-Doppler sidelobes, a two-dimensional MMF (2-D MMF) is proposed, and the relevant signal-to-noise ratio (SNR) loss is deduced. A cyclic algorithm is also designed to calculate the 2-D MMF for suppressing sidelobes over desired range-Doppler regions with constrained SNR loss and mainlobe width. Several simulations and an experiment based on real measured data of an airborne platform are conducted to illustrate the effectiveness of the proposed 2-D MMF.

This paper proposes a phase-derived velocity measurement (PDVM) method for high-speed targets based on wideband direct sampling linear frequency modulated radar. First, a high-speed target echo model considering intrapulse Doppler modulation is developed. Then, a PDVM model considering acceleration is established. The key to realizing PDVM is resolving phase ambiguity. Under low signal-to-noise ratio (SNR) conditions, a joint processing method combining acceleration information and multiframe data to solve phase ambiguity is proposed, which can significantly reduce the SNR requirement for PDVM. In this paper, the small-amplitude micromotion measurement capability of the proposed method is verified by simulation. Moreover, the measured data of a Ku-band ground-based radar are used to verify the applicability of the PDVM method under low SNR conditions and its feasibility to be applied to complex multi-scattering point targets. Both the simulation and experimental results show that the proposed method is suitable for high-speed targets with radial motion, including acceleration and jerk, and that the PDVM precision can reach the order of magnitude of centimeters per second or millimeters per second.

The Doppler sensitivity issue is an urgent problem to be solved for the phase-coded radar although it can give the promise of improved range resolution and resistance against various kinds of distortion. Due to the ideal autocorrelation and cross-correlation properties, the complementary sequence is utilised in high-frequency surface wave radar and MIMO radar. However, the Doppler frequency shift affects the autocorrelation property of the complementary sequence. This study aims to solve this problem. Based on the signal model and mathematical derivation, a new algorithm is proposed and the simulation results indicate the effectiveness of this method. This study also puts forward the signal processing diagram and the method to obtain the new code.

To deal with the problem of aerodynamic and stealth integrated optimization of DSI inlet, a multi-objective optimization study on aerodynamic and stealth of the DSI inlet is carry out which based on the deformation of the three-dimensional compression bump surface. The FFD parametric method is used to parameterize the bump surface; CFD calculation based on RANS equations is used to analyze the aerodynamic performance of the DSI inlet, large element physical optical method and uniform theory of diffraction are used to calculate RCS of the DSI inlet; And ASMOPSO algorithm with the Kriging surrogate model which based on the expect hyper-volume improvement infill criterion is adopted for integrated optimization design. The results of DSI inlet aerodynamic and stealth integrated optimization exhibit considerable improvement.

This paper presents an efficient multi-objective optimization method, focusing on aerodynamic optimization of a diverterless supersonic inlet (DSI) in transonic and supersonic flight conditions. The DSI inlet, through scrutinizing the Bump shape has potential to attain greater aerodynamic performance on exit plane of inlet. However, the high cost of computational fluid dynamic (CFD) simulations raises a significant challenge in the DSI optimization process. In order to obtain solution set in few numbers of objective function calls, a meta-model multi-objective particle swarm optimization (MOPSO) method is proposed based on a self-adaptive Kriging surrogate model, and applied to solve this kind of costly black-box optimization problem. The Kriging model is updated by using a dynamic expected hyper-volume improvement (EHVI) sample metric, which is developed by analyzing disadvantages of the original sample criterion. With the help of the dynamic sample metric, simulation results show that the surrogate-based MOPSO algorithm can obtain plenty enough non-dominated solutions and achieve high precision in the approximation of the Pareto front. In terms of DSI inlet optimization, the bump shape is parameterized by free form deformation (FFD) method, and the total pressure distortions of inlet exit plane are treated as two minimization objectives under transonic and supersonic flight conditions. A well distributed non-dominated solution set is generated by the proposed algorithm within the context of a small call number of cost evaluations, and optimized inlet configurated by the selected solution has better aerodynamic characteristics compared with the initial inlet.

The multi-objective particle swarm optimization algorithm (MOPSO) has been applied and modified for optimal designs in various engineering fields. However, the intimal algorithm is still has the problems of low accuracy and poor diversity of solutions as it is easy to fall into local optimum in the later evolution stage. A new dynamic mutation operator has been established based on the α-stable distribution theory and incorporated with multi-objective particle swarm optimization algorithm(ASMOPSO). By using random Numbers which generated by the α-stable distribution, the population of PSO algorithm was mutated. And this mutate operation increases the diversity of the population. Because the stability coefficient in the ASMOPSO algorithm can change the range and amplitude of the mutation. This operation makes the new algorithm has the ability to balance the calculation accuracy and global optimization. Several benchmark functions test show that the ASMOPSO algorithm has fast global optimization ability. The proposed algorithm is applied to the multi-objective aerodynamic optimization design of RAE2822 transonic airfoil. The comparison results also show that ASMOPSO algorithm is more excellent than the basic MOPSO algorithm.

Micromotion features of a target contain unique structural information and motion information about the target, which can be used as an important basis for target recognition. One of the technical bottlenecks for micromotion feature extraction is achieving a fine characterization of the target motion state. With the high-precision range and velocity measurement, this paper uses the phase-derived method to reconstruct the motion state of the target and realize accurate translational compensation for the target. At the same time, the high range resolution of wideband radar is used to effectively extract target scattering points with micromotion from the perspective of the one-dimensional high range resolution profile and the two-dimensional inverse synthetic aperture radar (ISAR) image. On this basis, reliable micromotion feature extraction can be achieved by using the slow variability of the target motion and eliminating the translational or rotational information of the target. The performance of the high-precision range and velocity measurement and the feasibility of the micromotion feature extraction based on phase-derived range and velocity measurement are verified by simulation results. Then, the effectiveness of the proposed algorithm is further verified by carrying out a steel ball ejection experiment and a civil aviation aircraft experiment.

Background: As the results of previous systematic reviews and meta-analyses on acupuncture for polycystic ovary syndrome (PCOS) have provided inconsistent evidence. This overview of systematic reviews (SRs) and meta-analyses will aim to critically appraise the methodology and reporting quality of the relevant SRs and meta-analyses with the aim of identifying whether acupuncture could provide an effective treatment for patients with PCOS or not. Methods: Electronic databases including MEDLINE via Ovid, EMBASE, PubMed, Cochrane library, China National Knowledge Infrastructure (CNKI), Chinese Scientific Journal Database (VIP database), and Wanfang Database will be searched for related SRs and meta-analyses from inceptions to the search date without language restrictions. Two reviewers will independently select SRs and meta-analyses and collect related data, and a third reviewer will be introduced if any disagreement happened during the assessing. The Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) and the latest Assessment of Multiple Systematic Reviews 2 (AMSTAR2) checklists will be employed to evaluate the reporting and methodology quality. Results: This overview will be published in a peer-reviewed journal. Conclusion: This overview will identify related SRs and meta-analyses of acupuncture for treating PCOS. Ethics and dissemination: Ethics approval and patient consent are not required as this study is an overview based on published systematic reviews and meta-analyses.

The existing methods for motion compensation in inverse synthetic aperture radar (ISAR) imaging are generally limited to the low-order target motion model, and require iterative optimization with limited velocity estimate precision and heavy computational burdens. This paper proposes a high-precision method of phase-derived velocity measurement (PDVM) and applies it to motion compensation of ISAR imaging. The method applies PDVM based on range profiles cross correlation to the translational velocity estimation of targets, and converts the velocity measurement results to the corresponding range increment. The equivalent phase-derived range measurement precision can reach the order of magnitude of millimeter (mm) or even sub-mm, which can satisfy the precision requirements of both envelope alignment and phase adjustment. The key to realizing PDVM is resolving phase ambiguity. The traditional method for resolving ambiguity has very high requirements for the signal-to-noise ratio (SNR). This work resolves ambiguity by combining multiframe data, i.e., by resolving ambiguity of multiframe data simultaneously instead of resolving ambiguity of single-frame data independently and correcting the above ambiguity-resolving results using a minimum-entropy method. Therefore, phase ambiguity can be correctly resolved under a relatively low SNR. Experimental results of an ISAR imaging of an airplane show that the method proposed in this paper can obtain high-quality ISAR imagery, and can efficiently realize robust imaging under the conditions of low SNR.

The challenges of the most multi-objective particle swarm optimization (MOPSO) algorithms are to improve the selection pressure, equilibrate the convergence and diversity when tackling large-scale many-objective problems. To overcome these challenges, this paper proposes a novel PSO-based large-scale many-objective algorithm, named as LMPSO. In LMPSO, the Alpha-stable mutation is performed to enhance the diversity of swarm for avoiding premature convergence. And the parameters of PSO and Alpha-stable mutation are dynamically set following the Logistic function, which emphasize different convergence and diversity at different optimization stages. Moreover, LMPSO adopts a fitness to maintain the external archive, and the calculation of fitness is based on binary additive epsilon indicator. The binary indicator is also used to update the personal best of particles to avoid wrongly selecting dominance resistance solutions (DRSs). Aims for improving the selection pressure, the proposed algorithm employs a concept of dominance resistance error to identify the DRSs. To verify this idea, the DTLZ, ZDT, and LSMOP test suites with up to 1000 decision variables and 10-objective are used to qualify the performance of LMPSO. The simulations reveal the fact that the LMPSO significantly outruns the several chosen state-of-the-art algorithms when solving large-scale many-objective test instances.

Background Bee venom acupuncture has been used in treating patients with shoulder adhesive capsulitis, yet the effectiveness and safety remains unclear. Therefore, this systematic review will aim to assess the effectiveness and safety of bee venom acupuncture for shoulder adhesive capsulitis. Methods Electronic databases including EMBASE, PUBMED, the Cochrane Central Register of Controlled Trials, China National Knowledge Infrastructure, Chinese Scientific Journal Database, Wanfang Database, and Chinese Biomedical Literature Database will be searched for relevant randomized controlled trials from their inception to the search data without language and publication status. Randomized controlled trials involving bee venom acupuncture for treating shoulder adhesive capsulitis will be included. The primary outcome will be pain visual analogue scale, and secondary outcomes include active and passive range of motions, shoulder pain and disability index. Meta-analysis will be conducted using Review Manager software (V.5.3). The results will be presented as risk ratio for dichotomous data, and standardized or weighted mean difference for continuous data. Results The results will be disseminated through a peer-reviewed journal publication. Conclusion These systematic review findings will provide an evidence of bee venom acupuncture for shoulder adhesive capsulitis, and help to inform clinical practitioners and policy-makers in the decision-making. Ethics and dissemination Ethics approval and patient consent are not required as this study is a systematic review based on published articles.

In order to balance the global and local search ability of the basic particle swarm optimization (PSO) in the evolution loop, an alpha-stable distribution is adopted and applied to perform mutate operation in PSO. The development of a new dynamic mutation particle swarm optimization algorithm was established by the alpha-stable mutation. By dynamically modifying the stability coefficientof alpha-stable function, the amplitude and intension of the mutate operation is adjusted adaptively, and the global optimization ability of PSO is improved. The new algorithm is compared with DE and PSO on seven test functions . Simulation results show that the alpha-stable PSO algorithm have a faster convergence speed and a better global optimization performance in low, medium and high dimension problems. The proposed algorithm is applied to drag reduction design of RAE2822 transonic airfoil and compared with PSO algorithm. The comparison results also show that our algorithm is more excellent than basic PSO.