Compared to large-scale MIMO radar, coprime MIMO radar can achieve approximate estimation performance with reduced antenna number. In this paper, joint direction of arrival (DOA) estimation and array calibration for coprime multiple-input multiple-output (MIMO) radar is considered, and an iterative method for the estimations of DOA and array gain-phase errors is proposed. Based on the received data structure of coprime MIMO radar, trilinear decomposition is firstly adopted to obtain the estimations of transmit and receive direction matrices, which are perturbated by the gain-phase errors. Through equation transformation, the un-perturbated direction matrices and gain-phase errors can be iteratively updated based on Least squares (LS). Finally, the unique DOA estimation is determined from the intersection of transmit and receive direction matrices. The proposed algorithm achieves better DOA estimation and array calibration performance than other methods including estimation of signal parameters via rotational invariance techniques (ESPRIT)-like algorithm, multiple signal classification (MUSIC)-like algorithm and joint angle and array gain-phase error estimation (JAAGE) method, and it performs close to the method with ideal arrays. Multiple simulation results verify the algorithmic effectiveness of the proposed method. 相似文献
随着无人机软硬件技术的发展,多无人机集群自组织形成的无人机自组网(Flying Ad-Hoc networks, FANETs)受到了越来越多的来自学术界和工业界的关注,其灵活的部署和快速的反应能力使其能高效地完成多种多样的任务。而无人机自组网路由协议是提高服务质量(Quality of service, QoS)最重要的方法之一,但无人机自组网的移动性和动态性给路由协议的设计带来了严峻的挑战。传统的移动路由协议不能很好地满足无人机自组网的路由需求,因此研究者们从基于拓扑、地理和分层的角度提出了各式各样的无人机自组网路由协议,旨在克服移动性和提高网络的服务质量,并指出未来无人机自组网的路由协议可以考虑机会路由、软件定义网络(Software defined network,SDN)决策和预测驱动决策等综合提高QoS。本文主要针对无人机自组网网络特征,从不同的路由方法出发,SDN对路由协议进行总结和归纳,并对未来的研究方向进行了展望。 相似文献
World Wide Web - In this paper, we first study the problem of Correlation-aware Task computation offloading (CoTask) in mobile edge computing. Specifically, considering the correlation among... 相似文献
Generally, multi-dimensional spectral peak search (SPS) in parameter estimation for polarization sensitive coprime linear arrays (PS-CLAs) requires heavy computational burden. To resolve this problem, we propose a search-free algorithm for multi-parameter estimation with PS-CLAs in this paper. Specifically, different from the decomposition algorithms, we first reconstruct the total received signal of PS-CLA as the signal extracted from a large uniform linear array, which enables to offer a spectrum function only with regard to direction of arrival (DOA) by utilizing rank reduction estimator. Subsequently, we employ the polynomial root finding technique instead of one-dimensional SPS to directly calculate the DOA estimates. Furthermore, a quadratic optimization problem is established for the polarization parameters and in particular, the closed-form solutions are provided by utilizing Lagrange multiplier approach. Finally, numerical simulations illustrate that the proposed search-free algorithm can obtain improved estimation accuracy with remarkably low complexity.