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Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Massive multiple input multiple output (MIMO) is one of the key technologies, as 5G and future mobile wireless networks continue to evolve. With the increasing number of antennas, the design of receivers has brought a huge challenge, and detection algorithms with too much complexity are difficult to be applied in practice. In this paper, a high-parallelism (HP) detection algorithm is developed into a neural network, the single-layer neural network is based on each iteration of this algorithm, which is combined with trainable weighted parameters and nonlinear neural units, and the network structure HP-Net is proposed. Optimal trainable parameters are obtained by training the HP-Net, which in turn improves the detection performance. The experimental results show that the paper method is less complex and can obtain lower bit error rate (BER) than the traditional minimum mean square error (MMSE) algorithm, and has better BER performance than the HP detection algorithm. [ABSTRACT FROM AUTHOR]

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Aiming at the problem of multi-polarization reception and occlusion effects of conformal arrays on complex carriers, this paper proposes an improved polarization multiple signal clasritication (MUSIC) algorithm based on the pattern matrix reconstruction steering vector. First, we model the conformal antenna array. Then, afier the arimuth and elevation component pattern data of each element are obtained, the pattern data is decomposed and reconstrucied to the steering vector matrix of the array. Finally, we estimaie the direction of arrival (DOA) and polarization parameters by the polarization MUSIC algorithm. Compared with the polarization MUSIC algorithm based on the theoretical sieering vector, the improved algorithm proposed in this paper has higher estimation accuracy while avoiding the ocdition effect. It also can reduce the amount of calculation. The condition is verified by simulation experiments. [ABSTRACT FROM AUTHOR]

To improve the performance of sparse recovery space-time adaptive processing (SR-STAP) algorithms with both array gain/phase errors and grid mismatches, a sparse Bayesian learning-based robust SR-STAP approach is proposed in this paper. Firstly, the SR-STAP signal model with mismatched errors is constructed using the Kronecker structure of the space-time steering vector. Secondly, the angle-Doppler profile and mismatched parameters are alternatively achieved by utilizing the Bayesian inference and expectation-maximization algorithm. Finally, the precise clutter-plus-noise covariance matrix is estimated and the corresponding weight vector is calculated with the above obtained parameters. Simulation results verify that the proposed algorithm can significantly improve the target detection performance with mismatched sparse signal model. [ABSTRACT FROM AUTHOR]

Distributed electromagnetic target identification aims to realize traditional centralized electromagnetic target identification by using technologies such as distributed optimization and distributed computing. The distributed optimization method combines the distributed computing architecture to realize the distributed solution to the optimization problem, and realizes the mapping from the problem information and data to the optimal target identification model in a distributed manner. This paper uses the decentralized stochastic gradient descent, which is a classical distributed optimization method, to establish a distributed computing architecture and a distributed electromagnetic target identification method for electromagnetic target identification. Based on the actual electromagnetic signal data, the effectiveness of the proposed algorithm is verified. When the performance of the distributed electromagnetic target identification algorithm and the centralized identification algorithm remains above 90%, the single node training time decreases by more than 50%, which significantly improves the training efficiency. [ABSTRACT FROM AUTHOR]

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

How to solve the task scheduling problem under resource constraints to ensure the efficient execution of multiple tasks in the presence of conflicts in resource use, among which reasonable task scheduling and resource conflict resolution are the key factors that affect the effect of task execution. Based on the workflow graph model, a framework for task scheduling under resource constraints is proposed, and for resource conflicts generated in the scheduling process, two task scheduling algorithms are proposed; one algorithm determines priority by task criticality, is based on greedy thinking and adjusting the topological structure of the workflow graph, and determines the task scheduling plan before the task starts; the other algorithm adopts the flexible resource scheduling method, so that the conflicting task will be executed first under the condition of insufficient resources, and the task will be scheduled and executed alternately. Finally, the feasibility of related algorithms is verified through earthquake rescue cases, contrasting experiments with typical representatives of two types of typical resource-constrained project scheduling algorithms are conducted, and the advantages and significance of the two algorithms proposed in this paper are analyzed. The simulation results show that the algorithm proposed in this paper has the advantage of being suitable for cases with the shortage of earthquake rescue resources. [ABSTRACT FROM AUTHOR]

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Long-time coherent integration is one of the important techniques to improve radar detection performance. The range migration (RM), range curvation (RC), Doppler frequency migration (DFM) and Doppler frequency curvation (DFC) induced by the movement of high-speed maneuvering target during the longtime coherent integration would bring about serious integration signal-to-noise ratio (SNR) loss, which may furthermore cause the target detection performance of the radar sharp deterioration in the background of noise. In order to solve the problem, the paper proposes a parameterized long-time integration algorithm for high-speed maneuvering targets. The method applies keystone transform (KT) to eliminate linear RM firstly. Then coherently integrated modified cubic phase function (CIMCPF) and coherency integrated modified high-order ambiguous function (CIMHAF) methods are utilized respectively to estimate the first-order and second-order accelerations. Thanks to the use of signal coherent property, the method is still effective at low signal-to-noise ratio. Furthermore, since there is no brute-force search process, the computational complexity of the method is low. Simulation results and analysis demonstrate the excellent performance of the proposed method. [ABSTRACT FROM AUTHOR]

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Convolutional codes are often used as sub-codes of high performance codes such as concatenated codes and turbo codes. Correct parameter estimation of convolutional codes is the basis of recognition of concatenated codes and turbo codes, which requires that the estimation algorithms of convolutional codes should have strong robustness against channel noise. The key to such purpose is to make use of the soft-decesion demodulation received sequence. In this paper, a cost function model based on exponential function is proposed according to the linear constraint relation between symbols of recursive systematic convolutional codes. The parameter estimation of convolutional codes is transformed into the minimal value of the cost function. And the optimization is accomplished via a simple iterative process by conjugate gradient. Simulation results show that, compared with the existing algorithms, the new algorithm significantly improves the performance while it is also applicable to the estimation of general convolutional codes and has a fast convergence speed. [ABSTRACT FROM AUTHOR]

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In order to solve the problems of halo artefacts and unfavourable visual perception in the fused images, this paper proposes an image fusion algorithm based on gradient-domain guided filtering and an improved pulse-coupled neural network (PCNN). First, an image fusion model is constructed using the image features of image structure, sharpness and contrast saliency. Secondly, the initial decision map is optimised by inter-pixel correlation using gradient-domain guided filtering instead of the traditional optimisation method. Then, the optimised decision map is used as external input to stimulate the improved PCNN model to obtain the fusion weight map. Finally, the source image and the fusion weight map are weighted to obtain the final Finally, the source image and the fusion weight map are weighted to obtain the final fused image. The experimental results show that this method can better preserve the image edge, texture and detail information, avoid halo artefacts on the target edge, and facilitate visual observation. [ABSTRACT FROM AUTHOR]

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Elasric oprical networks (EONs), as the promiring next generation oprical networks, have received extenrive attention in recent years. Rouiing and spectrum allocation (RSA) is one of the core technologies for network derign and control. This paper systematically analyzes the concept of EONs and describes the key issue of RSA in detall. From the static and dynamic perspective, state-of-the-art RSA algorithms are summarized and into the exact algorithm, the intelligent optimization algorithm, the heuristic algorithm, and the learning-based algorithm on the baris of the algorithmic framework wtth different characteristics. Combined wtth the future application requirements of EONs, the difficulties and challenges faced by the RSA algorithm are discussed, and the development trend of the RSA algorithm is prospected. [ABSTRACT FROM AUTHOR]

As a wideband radar syrtem, the synthetic aperture radar (SAR) usually confiirts wrth other elertromagnetic syrtems working in the same frequency bands. These iignais, mort of which are natrow-band interference (NBI) for SAR syrtems, severely mterfere SAR syrtems to generate a high-resolution image. Many previous research results focused on the NBI suppresion problem, however, few of them noticed that the NBIs may be time-varying in a local region among different puises, which restricts the suppresion performance of some llasi methods. Hence, in this paper, a graph Lapladan embedding (GLE) algorithm is proposed to suppress NBIs by constructing the Laplaian embedding connertions between different puises of iignais. As a resuk, locally time-varying interferences are embedded in a nonlinear low-dimenional manifold and can be effectively mitigated. The real SAR data measured with NBI are processed, and the resufrs show the effiiency of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Aiming at the body-frame velocity-aided Vb in-motion inertial-frame alignment of the strapdown inertial navigation system (SINS) in polar regions, this paper proposes the double-velocity inertial-frame alignment with the pseudo inertial navigation system (INS) modeling. With the proposed algorithm, the enlargement of polar navigation errors caused by the INS modeling and the errors of alignment modeling in the process of traditional inertial-frame alignment can be eliminated to improve the performance of the polar alignment. Finally, the semi-physical car experiments in low latitude region and the simulations in polar regions are conducted. In the initial latitudes 75° and 85°, the mean absolute error (MAE) and standard deviation (STD) of 50 alignment results with the proposed algorithm are 0. 507 2°, 2. 527 3° and 0. 605 2°, 2. 875°, respectively. Consequently, the proposed algorithm would be feasible and favorable and the problems arise in polar INS modeling and the inertial-frame alignment modeling can be handled. Then the performance of the polar alignment can be improved. [ABSTRACT FROM AUTHOR]

Attitude calculation is the core part of inertial navigation. When the output of the inertial group is the angular rate, this paper refers to the idea of the monadic attitude algorithm. In the angular velocity polynomial fitting process, the angular velocity polynomial information of the previous period is used to integrate the angular velocity polynomials in multiple different fitting intervals. The angle increment information corresponding to the sampling period is extracted, and then the angle rate information and the angle increment information after multiple corrections are used to construct a cone error compensation structure. The simulation results show that the new algorithm can not only increase the attitude update frequency of the traditional angular rate attitude algorithm, but within a certain cone frequency range, the calculation accuracy of the traditional algorithm is improved by 2 to 3 orders of magnitude. [ABSTRACT FROM AUTHOR]

This paper analyzes the current situation of satellite trace, telemetry, control (TT & C) resource scheduling problem. Based on the existing scenarios, requirements and tasks, we establish the objective constraint satisfaction model. After the systematic description of TT & C resources, visible arcs and task requirements, considering the complex relationship between TT & C task requirements, a TT & C resources scheduling algorithm based on task conflict avoidance is proposed. Compared with other traditional methods, this algorithm has considered the resource requirements of global tasks and the complex correlation between tasks. We introduce the acceptance function of the feasible solution, which avoids the greedy drawbacks of the traditional heuristic algorithm. Experimental results show that the algorithm can raise the scheduling success rate of tasks effectively when applied to a large-scale TT & C task resource scheduling. [ABSTRACT FROM AUTHOR]

For the stabilization control problem of the vessel-borne platform in the presence of dynamic uncertainties and unknown external disturbances, this paper proposes the super-twisting extended stale observer (STESO) based super-twisting sliding mode (STSM) stabilization control strategy. The STESO is constructed to online estimate the total disturbances lumped by the dynamic uncertainties and the unknown external disturbances of the vessel-borne stabilization platform. Based on the above, the STSM stabilization control law of the vessel-borne platform is designed by employing the super-twisting algorithm. The upper support surface of the vessel-borne platform is asymptotically adjusted to the desired position and attitude in the inertial space and is kept to be unchanged. The simulation results with comparisons demonstrate the higher robustness of the designed vessel-borne platform stabilization control taw and the higher disturbance estimation and stabilization control accuracy. [ABSTRACT FROM AUTHOR]

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)