并行工程产品开发过程的建模方法学

在并行工程中，为了实现产品开发过程的集成、并行和最优化，首先要建立能够充分反映产品开发过程各方面信息的产品开发过程模型。通过对模型的仿真分析和优化，指导产品开发过程的实施。本文首先提出了并行工程产品开发过程模型是集成多视图模型，随后提出了采用集成多视图建模理论的并行工程产品开发过程建模、分析和管理的方法学框架     

Parsimonious Mean-Covariance Modeling for Longitudinal Data with ARMA Errors

Based on the generalized estimating equation approach, the authors propose a parsimonious mean-covariance model for longitudinal data with autoregressive and moving average error process, which not only unites the existing autoregressive Cholesky factor model and moving average Cholesky factor model but also provides a wide variety of structures of covariance matrix. The resulting estimators for the regression coefficients in both the mean and the covariance are shown to be consistent and asymptotically normally distributed under mild conditions. The authors demonstrate the effectiveness, parsimoniousness and desirable performance of the proposed approach by analyzing the CD4+ cell counts data set and conducting extensive simulations.     

SKIES AND MONADS

In ~*R_+,we define(↑↓)~-equivalence similar to that given by Puritzfor ~*N,and callthe(↑↓)~-equivalence classes skies.For x∈~*R_+,let μ(x)be the monad of x defined by Watten-Wattenberg,and let(?)(x)=sup{|y-z|/y,z∈μ(x)}∈~*R.Then it is proved that x↑↓y iff(?)(x)=(?)(y).Furthermore,sup{y/y↑↓x}=(?)(x)~(-1),and (?)(x)~2=(?)(x).     

Information identification in different networks with heterogeneous information sources

Traditional cheaptalk game model with homogeneous information sources provided a con clusion that dishonest information sources will not be identified if he changes strategy stochastically. In this paper, the authors incorporate different information diffusion networks and heterogeneous in formation sources into an agentbased artificial stock market. The obtained results are different with traditional results that identification ability of uninformed agents has been highly improved with diffu sion networks and heterogeneous information sources. Additionally, the authors find uninformed agents can improve identification ability only if there exists a sufficient number of heterogeneous information sources in stock market.     

Optimal pricing and inventory policy with order cancelations under the cash-on-delivery payment scheme

Considering a periodic review system where the online seller allows the customers to pay when the products are delivered to them（referred as cash-on-delivery payment scheme in this paper）,the authors investigate the seller＇s joint pricing and inventory control policy with a finite planning horizon.In particular,the authors incorporate the customers＇ possible order cancellation behavior with the cash-on-delivery scheme.It can be proven that the base-stock list price policy is optimal under mild conditions.The authors also analyze the impact of the customers＇ forward looking behavior on the optimal policy.     

Self-alignment of full skewed RSINS：observability analysis and full-observable Kalman filter

Traditional orthogonal strapdown inertial navigation sys-tem （SINS） cannot achieve satisfactory self-alignment accuracy in the stationary base： taking more than 5 minutes and al the iner-tial sensors biases cannot get ful observability except the up-axis accelerometer. However, the ful skewed redundant SINS （RSINS） can not only enhance the reliability of the system, but also improve the accuracy of the system, such as the initial alignment. Firstly, the observability of the system state includes attitude errors and al the inertial sensors biases are analyzed with the global perspective method： any three gyroscopes and three accelerometers can be assembled into an independent subordinate SINS （sub-SINS）;the system state can be uniquely confirmed by the coupling connec-tions of al the sub-SINSs;the attitude errors and random constant biases of al the inertial sensors are observable. However, the ran-dom noises of the inertial sensors are not taken into account in the above analyzing process. Secondly, the ful-observable Kalman filter which can be applied to the actual RSINS containing random noises is established; the system state includes the position, ve-locity, attitude errors of al the sub-SINSs and the random constant biases of the redundant inertial sensors. At last, the initial self-alignment process of a typical four-redundancy ful skewed RSINS is simulated： the horizontal attitudes （pitch, rol ） errors and yaw error can be exactly evaluated within 80 s and 100 s respectively, while the random constant biases of gyroscopes and accelero-meters can be precisely evaluated within 120 s. For the ful skewed RSINS, the self-alignment accuracy is greatly improved, mean-while the self-alignment time is widely shortened.     

Higher-order principal component pursuit via tensor approximation and convex optimization

Recovering the low-rank structure of data matrix from sparse errors arises in the principal component pursuit （PCP）. This paper exploits the higher-order generalization of matrix recovery, named higher-order principal component pursuit （HOPCP）, since it is critical in multi-way data analysis. Unlike the convexification （nuclear norm） for matrix rank function, the tensorial nuclear norm is stil an open problem. While existing preliminary works on the tensor completion field provide a viable way to indicate the low complexity estimate of tensor, therefore, the paper focuses on the low multi-linear rank tensor and adopt its convex relaxation to formulate the convex optimization model of HOPCP. The paper further propose two algorithms for HOPCP based on alternative minimization scheme： the augmented Lagrangian alternating direction method （ALADM） and its truncated higher-order singular value decomposition （ALADM-THOSVD） version. The former can obtain a high accuracy solution while the latter is more efficient to handle the computationally intractable problems. Experimental results on both synthetic data and real magnetic resonance imaging data show the applicability of our algorithms in high-dimensional tensor data processing.     

Multi-dimensional scattering properties diagnosis system of scale aircraft model in an anechoic chamber

Aiming at the concept of ＂diagnosis＂, a simple and effective broadband radar cross section （RCS） measurement system is constructed, and some multi-dimensional scattering properties diagnosis techniques are presented based on the system. Firstly, a stepped-frequency signal is employed to achieve high range resolution, combining with a variety of signal processing tech- niques. Secondly, cross-range resolution is gained with a rotating table, and the high-resolution two-dimensional （2-D） imaging of the scale model is obtained by the microwave imaging theory. Finally, two receiving antennas with a small distance in altitude are used, and the three-dimensional （3-D） height distribution of scattering points on the scale model is extracted from the phase of images. Some typical bodies and a scale aircraft model are diagnosed in an anechoic chamber. The experimental results show that, after scaling with a metal sphere, the accurate one- dimensional （l-D） RCS pattern of the model is obtained, and it has a large dynamic range. When the bandwidth of the transmitting signal is 4 GHz, the resolution of the 2-D image can reach to 0.037 5 m. The 3-D height distribution of scattering points is given by interferometric measurement. This paper provides a feasible way to obtain high-precision scattering properties parameters of the scale aircraft model in a conventional rectangular anechoic chamber.     

Multi-target localization for bistatic MIMO radar in the presence of unknown mutual coupling

A decoupling-estimation signal parameters via rotarional invariance technique(ESPRIT) method is presented for multi-target localization with unknown mutual coupling in bistatic multiple-input multiple-output(MIMO) radar.Two steps are carried out in this method.The decoupling operation between angle and mutual coupling estimates is realized by choosing the auxiliary elements on both sides of the transmit and receive uniform linear arrays(ULAs).Then the ESPRIT method is resilient against the unknown mutual coupling matrix(MCM) and can be directly utilized to estimate the direction of departure(DOD) and the direction of arrival(DOA).Moreover,the mutual coupling coefficient is estimated by finding the solution of the linear constrained optimization problem.The proposed method allows an efficient DOD and DOA estimates with automatic pairing.Simulation results are presented to verify the effectiveness of the proposed method.     

Dynamic model and simulation of aseismatic system about laser gyro strapdown inertial measure assembly based on MSTMM

The precision of the laser gyro used in tactical missiles is poor because of dithering frequency,actuating by vibration,shock and overload in dynamical environment.This paper introduces the transfer matrix method of the multibody system(MSTMM),establishes the dynamic model of the laser gyro strapdown inertial measure assembly aseismatic system,and analyzes the precision affected by dithering of the laser gyro and shocking of the tactical missile.And the dynamic response of the laser gyro strapdown inertial measure assembly aseismatic system is obtained by simulating the multibody system model.The simulation result indicates a theoretical idea to design the vibration isolation for the laser gyro strapdown inertial measure assembly.