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研究了航空发动机在线优化算法问题。基于序列可行方向法,提出了一种用于解决一般非线性优化问题改进的序列线性规划(SLP)在线优化算法——可行下降序列线性规划(FSLP)方法。其显著特点是通过适当的步长修正算法,在保证目标函数下降的同时,确保解的可行性。根据对偶理论证明了其核心算法的收敛性,对步长修正原理进行了数学分析,并详细介绍了算法实现途径。基于上述优化算法,以某型双转子涡扇发动机最大推力模式为仿真算例,验证了该算法在解决航空发动机在线优化问题时,相比传统的序列优化方法,在提高优化算法解的可行性方面效果更好。 相似文献
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States of dynamic models with a higher order memory are estimated using both a stack sequential decoding algorithm and the Viterbi decoding algorithm (VDA), without higher dimensional dynamic system representation. This results in memory reduction for state estimate implementation. It is found that state estimation with a stack sequential decoding algorithm is faster and more practical than the state estimation with the Viterbi decoding algorithm, even though the estimates obtained by the Viterbi decoding algorithm are superior 相似文献
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在分析已有的Sage-Husa自适应滤波算法的基础上,本文首先推导了两种量测噪声自适应估计方法的等价性。为充分利用组合系统中已知的部分量测噪声参数,提高滤波稳定性和精度,研究了基于序贯结构的Sage-Husa自适应滤波算法;当组合系统测量噪声参数均为已知时,为降低算法复杂度,提高Sage-Husa自适应滤波的鲁棒性,加入协方差匹配的方法对序贯结构的Sage-Husa自适应滤波算法进行改进;通过在序贯结构下采用相应的信息融合策略,充分利用组合系统的输出信息。将两种算法分别应用于MIMU/GPS/磁强计组合系统中,基于跑车实验的离线数据分析表明,第一种滤波算法的滤波稳定性较标准自适应算法在滤波稳定性上有明显提高;第二种改进的滤波算法既降低了算法复杂度,又提高了抗野值效果,有效保持了组合系统在干扰状态下的导航精度。 相似文献
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A signal processing technique is proposed for improving position-fix navigation system accuracy performance when the geometry of the navigation landmarks (e.g. sensors) are nearly collinear. In the navigation literature, the accuracy degradation associated with a nearly collinear measure geometry is termed the geometric dilution of precision (GDOP). Its presence causes not only the variance of the position estimates to be highly inflated but also any bias terms which may be present in the model. Since a nearly collinear predictor matrix is mathematically equivalent to GDOP, it is proposed to use the ridge regression technique in a navigation signal processor. A position-fix algorithm based on ridge regression reduces the bias and variance inflation caused by GDOP and the overall mean-squared position error as well. Ridge regression contains the GDOP-sensitive least-mean-square (LMS) estimator as a special case. Even with a matched model, GDOP can inflate the mean-square error (MSE) of the ordinary least-squares estimator, whereas the ridge regression technique chooses a suitable biased estimator that will reduce the MSE, which is the main goal. The ridge concept is extended to include GDOP-amplified bias errors. A simple range/range navigation system is analyzed to illustrate the underlying principles of ridge regression 相似文献
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Xuejun Liao Runkle P. Carin L. 《IEEE transactions on aerospace and electronic systems》2002,38(4):1230-1242
An approach to identifying targets from sequential high-range-resolution (HRR) radar signatures is presented. In particular, a hidden Markov model (HMM) is employed to characterize the sequential information contained in multiaspect HRR target signatures. Features from each of the HRR waveforms are extracted via the RELAX algorithm. The statistical models used for the HMM states are formulated for application to RELAX features, and the expectation-maximization (EM) training algorithm is augmented appropriately. Example classification results are presented for the ten-target MSTAR data set. 相似文献
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Upadhyay T.N. Damoulakis J.N. 《IEEE transactions on aerospace and electronic systems》1980,(4):481-491
The design, implementation, and performance of a real-time estimation algorithm, referred to in this paper as the sequential piecewise recursive (SPWR) algorithm, for the global-positioning system (GPS) low-dynamics navigation system is described. The SPWR algorithm for this application was implemented in single precision arithmetic (32 bit, floating point). Numerical results are presented covariance and filter gains at a slower rate than the state measurement update, and it uses U-D factor formulation to perform covariance computations. The SPWR algorithm saves real-time processing requirements without appreciable degradation of filter performance. Another important feature of the SPWR algorithm is that it incorporates pseudorange and delta-range data from each GPS satellite sequentially for navigation solution. The SPWR algorithm, for this application, was implemented in single precision arithmetic (32 bit, floating point). Numerical results are presented. 相似文献
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考虑多类维修优先权的多级维修供应系统库存控制 总被引:1,自引:0,他引:1
备件筹措与保障站点的维修能力和故障件维修机制密切相关。在经典VARI-METRIC模型上,拓宽了模型中"无限维修总体"和"先到先修"的假设条件,基于排队理论,考虑维修优先权对维修过程的影响,对故障件的维修周转时间进行了修正,建立了具有多类维修优先权的备件初始库存优化模型。构造了多站点优先权分配的目标函数,采用智能优化算法对优先权分配方案进行了优化;根据所得方案,采用边际优化算法进行了备件库存优化,提出了采用智能优化算法和边际优化算法对优先权分配方案和备件库存进行分步优化的方法,并开展了算法复杂度分析。算例分析表明,考虑优先权的备件配置方案在满足各项保障效能指标的同时,显著降低了备件购置费用;分步优化的方法在有效降低运算时间提高计算效率的同时保持了一定的计算精度。提出的模型和优化方法能够为装备保障人员制定合理的保障方案提供决策支持。 相似文献
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The formulation of the decision making process of a failure detection algorithm as a Bayes sequential decision problem provides a simple conceptualization of the decision rule design problem. As the optimal Bayes rule is not computable, a methodology that is based on the Bayesian approach and aimed at a reduced computational requirement is developed for designing suboptimal rules. A numerical algorithm is constructed to facilitate the design and performance evaluation of these suboptimal rules. The result of applying this design methodology to an example shows that this approach is potentially a useful one. 相似文献
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Rao-Blackwellized粒子概率假设密度滤波算法 总被引:6,自引:1,他引:5
针对多目标跟踪(MTT),提出一种新的基于随机集的滤波算法,称为Rao-Blackwellized粒子概率假设密度滤波算法(RBP-PHDF)。算法运用Rao-Blackwellized思想,通过挖掘分析“混合线性/非线性模型”的结构,采用序列蒙特卡罗(SMC)方法预测与估计概率假设密度(PHD)迭代式中各个目标的非线性状态,并利用非线性状态粒子中包含的信息,使用卡尔曼滤波器(KF)对线性状态进行预测与估计。以更好地估计PHD进而提高各目标状态估计精度。分析与MTT仿真的结果表明,在相同的仿真条件下,与现有序列蒙特卡罗概率假设密度滤波算法(SMC-PHDF)相比,RBP-PHDF在降低粒子维数、减少计算量的同时,有效提升了估计精度。 相似文献
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主要研究了航空发动机性能寻优控制(PSC)算法问题。提出一种用于解决非线性约束优化问题的基于填充函数方法(FFM)的实时优化控制策略。通过构造填充函数,该算法可以在优化计算过程中能够不断跳出局部最优点,使得算法本身具备了全局寻优能力。详细介绍了其算法主要内容与实现途径,基于上述的填充函数优化算法,以某型涡扇发动机加力最小油耗优化控制模式为仿真算例,验证了该算法在解决航空发动机性能寻优控制问题时,相比传统的序列线性规划方法在全局寻优方面具有更好的效果。 相似文献
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He You Zhang Jingwei 《IEEE transactions on aerospace and electronic systems》2006,42(4):1359-1371
In order to resolve the problem of track-to-track association in a distributed multisensor situation, this paper presents independent and dependent sequential track correlation algorithms based on Singer's and Bar-Shalom's algorithms. Based on sequential track correlation algorithm, the restricted and attenuation memory track correlation algorithms and sequential classic assignment rules are proposed. In this paper, these algorithms are described in detail. Then, the track correlation mass and multivalency processing methods are discussed as well. Finally, simulations are designed to compare the correlation performance of these algorithms with that of Singer's and Bar-Shalom's algorithms. The simulation results show that the performance of these algorithms proposed here is much better than that of the classical methods under the environments of dense targets, interfering, noise, track cross, and so on. Under the above situations, their correct correlation ratio is improved about 69 percent over the classical methods 相似文献
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Image mosaicking is widely used in Geographic Information Systems (GISs) for large-scale ground surface analysis. However, most existing mosaicking methods can only be used in offline processing due to the enormous amounts of computation. In this paper, we propose a novel and practical algorithm for real-time infrared video mosaicking. To achieve this, a novel fast template matching algorithm based on Sum of Cosine Differences (SCD) is proposed to coarsely match the sequential images. The high speed of the proposed template matching algorithm is obtained by computing correlation with Fast Fourier Transform (FFT). We also propose a novel fast Least Squares Matching (LSM) algorithm for inter-frame fine registration, which can significantly reduce the computation without degrading the matching accuracy. In addition, the proposed fast LSM can effectively adapt for noise degradation and geometric distortion. Based on the proposed fast template matching algorithm and fine registration algorithm, we develop a practical real-time mosaicking approach which can produce seamless mosaic image highly efficiently. Experiments on synthetic and real-world datasets demonstrate that the proposed algorithm is not just computationally efficient but also robust against various noise distortions. 相似文献
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基于DMOM算法的航空发动机性能寻优控制 总被引:3,自引:0,他引:3
提出一种分散迁移优化算法(DMOM),可实现多峰值优化问题的全局最优解搜索.该算法通过随机选择参考粒子,不断迁移搜索自身所处区域峰值点,再通过分散操作排除局部最优点,重新生成新个体,可快速搜索到全局最优区域.将DMOM应用于航空发动机性能寻优控制仿真,结果表明:在最小油耗和最低涡轮温度模式下, DMOM的寻优速度相比遗传算法(GA)和粒子群算法(PSO)提高了2倍以上;同时DMOM的优化精度相比自组织迁移算法(SOMA)提高了60%以上,相比可行性序列二次规划(FSQP)算法提高了20%以上.验证了DMOM相比其他优化算法有更强的跳出局部最优的能力,在航空发动机最小油耗和最低涡轮温度这类多峰值寻优问题中具有明显的优势. 相似文献
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Blunt S.D. Gerlach K. Rangaswamy M. 《IEEE transactions on aerospace and electronic systems》2006,42(3):1043-1057
In the airborne space-time adaptive processing (STAP) setting, a priori information via knowledge-aided covariance estimation (KACE) is employed in order to reduce the required sample support for application to heterogeneous clutter scenarios. The enhanced FRACTA (FRACTA.E) algorithm with KACE as well as Doppler-sensitive adaptive coherence estimation (DS-ACE) is applied to the KASSPER I & II data sets where it is shown via simulation that near-clairvoyant detection performance is maintained with as little as 1/3 of the normally required number of training data samples. The KASSPER I & II data sets are simulated high-fidelity heterogeneous clutter scenarios which possess several groups of dense targets. KACE provides a priori information about the clutter covariance matrix by exploiting approximately known operating parameters about the radar platform such as pulse repetition frequency (PRF), crab angle, and platform velocity. In addition, the DS-ACE detector is presented which provides greater robustness for low sample support by mitigating false alarms from undernulled clutter near the clutter ridge while maintaining sufficient sensitivity away from the clutter ridge to enable effective target detection performance 相似文献
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In this paper, we present a novel and efficient track-before-detect (TBD) algorithm based on multiple-model probability hypothesis density (MM-PHD) for tracking infrared maneuvering dim multi-target. Firstly, the standard sequential Monte Carlo probability hypothesis density (SMC-PHD) TBD-based algorithm is introduced and sequentially improved by the adaptive process noise and the importance re-sampling on particle likelihood, which result in the improvement in the algorithm robustness and convergence speed. Secondly, backward recursion of SMC-PHD is derived in order to ameliorate the tracking performance especially at the time of the multi-target arising. Finally, SMC-PHD is extended with multiple-model to track maneuvering dim multi-target. Extensive experiments have proved the efficiency of the presented algorithm in tracking infrared maneuvering dim multi-target, which produces better performance in track detection and tracking than other TBD-based algorithms including SMC-PHD, multiple-model particle filter (MM-PF), histogram probability multi-hypothesis tracking (H-PMHT) and Viterbi-like. 相似文献