基于移动锚节点的无线传感网络节点定位算法
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摘要
在无线传感网络定位算法中,锚节点位置决定了节点定位精度。为此,提出基于高斯-Markov模型的移动锚节点的节点定位(GM-MAL)算法。GM-MAL算法基于高斯-Markov移动模型,提出自适应锚节点的移动路径规划,通过速度调整策略、垂直平分线策略、虚斥力策略以及虚引力策略规划路径。在定位阶段,将非凸优化问题转化为双凸形式,再利用交替最小算法(AMA)求解,进而获取更短的锚节点移动路径。实验数据表明,引入虚引力策略提高了路径规划精度,覆盖了更多的监测区域。此外,相比于线性算法,GM-MAL的定位精度得到提高。
The anchor node position plays an important role for accurate node localization in wireless sensor networks(WSNs). Therefore,a Gauss-Markov-based mobile anchor-localization(GM-MAL) algorithm is proposed in this paper. An adaptive mobile path planning of anchor node is proposed on the basis of Gauss-Markov mobility model. The strategies of velocity adjustment,perpendicular bisector,virtual repulsion and virtual attraction are used to plan the path in path planning stage. The non-convex optimization problem is converted into a bi-convex form,and solved with alternating minimization algorithm(AMA),which can acquire a shorter mobile path of anchor node. The experimental data shows that the virtual attraction strategy can improve the path planning accuracy,and cover more surveillance regions. In comparison with linear localization algorithm,the GM-MAL algorithm can improve the localization accuracy.
The anchor node position plays an important role for accurate node localization in wireless sensor networks(WSNs). Therefore,a Gauss-Markov-based mobile anchor-localization(GM-MAL) algorithm is proposed in this paper. An adaptive mobile path planning of anchor node is proposed on the basis of Gauss-Markov mobility model. The strategies of velocity adjustment,perpendicular bisector,virtual repulsion and virtual attraction are used to plan the path in path planning stage. The non-convex optimization problem is converted into a bi-convex form,and solved with alternating minimization algorithm(AMA),which can acquire a shorter mobile path of anchor node. The experimental data shows that the virtual attraction strategy can improve the path planning accuracy,and cover more surveillance regions. In comparison with linear localization algorithm,the GM-MAL algorithm can improve the localization accuracy.
引文
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[11] NOROOZI A,SEBT M A. Weighted least squares target location estimation in multi-transmitter multi-receiver passive radar using bistatic range measurements[J]. IET radar,sonar and navigation,2016,10(6):1088-1097.
[12] GODRICH H,HAIMOVICH A M,BLUM R S. Target localization accuracy gain in MIMO radar-based systems[J]. IEEE transactions on information theory,2010,56(6):2783-2803.
[2] NOROOZI A,SEBT M A. Target localization in multistatic passive radar using SVD approach for eliminating the nuisance parameters[J]. IEEE transactions on aerospace and electronic systems,2017,53(4):1660-1671.
[3] FISHLER E,HAIMOVICH A,BLUM R,et al. Spatial diversity in radars-models and detection performance[J]. IEEE transactions on signal processing,2006,54(3):823-838.
[4] GODRICH H,HAIMOVICH A M,BLUM R S. Target localisation techniques and tools for multiple-input multiple-output radar[J]. IET radar,sonar and navigation,2015,3(4):314-327.
[5] YANG H,CHUN J. An improved algebraic solution for moving target localization in noncoherent MIMO radar systems[J].IEEE transactions on signal processing,2016,64(1):258-270.
[6] LI J,STOICA P. MIMO radar with colocated antennas[J].IEEE signal processing magazine,2017,24(5):106-114.
[7] NOROOZI A,SEBT M A. A new estimator for elliptic localization in distributed MIMO radar systems[C]//Proceedings of2017 Iranian Conference on Electrical Engineering. Tehran:IEEE,2017:1615-1618.
[8] DIANAT M,TABAN M R,DIANAT J,et al. Target localization using least squares estimation for MIMO radars with widely separated antennas[J]. IEEE transactions on aerospace electronic systems,2013,49(4):2730-2741.
[9] EINEMO M,SO H C. Weighted least squares algorithm for target localization in distributed MIMO radar[J]. Signal processing,2015,115(4):144-150.
[10] NOROOZI A,SEBT M A. Target localization from bistatic range measurements in multi-transmitter multi-receiver passive radar[J]. IEEE signal processing letters,2015,22(12):2445-2449.
[11] NOROOZI A,SEBT M A. Weighted least squares target location estimation in multi-transmitter multi-receiver passive radar using bistatic range measurements[J]. IET radar,sonar and navigation,2016,10(6):1088-1097.
[12] GODRICH H,HAIMOVICH A M,BLUM R S. Target localization accuracy gain in MIMO radar-based systems[J]. IEEE transactions on information theory,2010,56(6):2783-2803.