Hybrid TDOA/FDOA and track optimization of UAV swarm based on A-optimality

The source location based on the hybrid time difference of arrival(TDOA)/frequency difference of arrival(FDOA) is a basic problem in wireless sensor networks, and the layout of sensors in the hybrid TDOA/FDOA positioning will greatly affect the accuracy of positioning. Using unmanned aerial vehicle(UAV) as base stations, by optimizing the trajectory of the UAV swarm, an optimal positioning configuration is formed to improve the accuracy of the target position and velocity estimation. In this pap...     

基于协议同步水下传感器网络目标协同定位算法

为了解决水下目标的定位问题,讨论了一种基于水下传感器阵列网络的目标协同定位算法。该算法在实现水下节点同步的基础上,通过建立目标位置与距离差测量值的统计模型后依据最大似然准则完成目标定位。定位算法的实现采用分布-集中相结合的处理方法,在提高定位精度的同时大大节省了水下节点通信能耗。通过仿真实验验证了算法的有效性和可行性,实验结果表明该方法具有较好的同步及目标定位精度。

Abstract：

A collaborative target location algorithm for underwater acoustic sensor networks （UASN） was proposed. The algorithm was achieved based on time synchronization for high transmitting delay for UASN. Target location was estimated by maximum-likelihood methods based on proposed statistical model which was established by the relation between target position and measured range difference. The proposed algorithm adopts the distributed-centralized computation methods,which degrade the transmitting energy comparing with traditional centralized methods. The result of simulation shows the application validity and the more location performance of the algorithm.     

Fuzzy Q learning algorithm for dual-aircraft path planning to cooperatively detect targets by passive radars

The problem of passive detection discussed in this paper involves searching and locating an aerial emitter by dualaircraft using passive radars. In order to improve the detection probability and accuracy, a fuzzy Q learning algorithrn for dual-aircraft flight path planning is proposed. The passive detection task model of the dual-aircraft is set up based on the partition of the target active radar＇s radiation area. The problem is formulated as a Markov decision process （MDP） by using the fuzzy theory to make a generalization of the state space and defining the transition functions, action space and reward function properly. Details of the path planning algorithm are presented. Simulation results indicate that the algorithm can provide adaptive strategies for dual-aircraft to control their flight paths to detect a non-maneuvering or maneu- vering target.     

Distributed localization for anchor-free sensor networks

Geographic location of nodes is very useful in a sensor network. Previous localization algorithms assume that there exist some anchor nodes in this kind of network, and then other nodes are estimated to create their coordinates. Once there are not anchors to be deployed, those localization algorithms will be invalidated. Many papers in this field focus on anchor-based solutions. The use of anchors introduces many limitations, since anchors require external equipments such as global position system, cause additional power consumption. A novel positioning algorithm is proposed to use a virtual coordinate system based on a new concept--virtual anchor. It is executed in a distributed fashion according to the connectivity of a node and the measured distances to its neighbors. Both the adjacent member information and the ranging distance result are combined to generate the estimated position of a network, one of which is independently adopted for localization previously. At the position refinement stage the intermediate estimation of a node begins to be evaluated on its reliability for position mutation; thus the positioning optimization process of the whole network is avoided falling into a local optimal solution. Simulation results prove that the algorithm can resolve the distributed localization problem for anchor-free sensor networks, and is superior to previous methods in terms of its positioning capability under a variety of circumstances.     

Grover quantum searching algorithm based on weighted targets

The current Grover quantum searching algorithm cannot identify the difference in importance of the search targets when it is applied to an unsorted quantum database, and the probability for each search target is equal. To solve this problem, a Grover searching algorithm based on weighted targets is proposed. First, each target is endowed a weight coefficient according to its importance. Applying these different weight coefficients, the targets are represented as quantum superposition states. Second, the novel Grover searching algorithm based on the quantum superposition of the weighted targets is constructed. Using this algorithm, the probability of getting each target can be approximated to the corresponding weight coefficient, which shows the flexibility of this algorithm. Finally, the validity of the algorithm is proved by a simple searching example.     

A hypersonic target coherent integration detection algorithm based on Doppler feedback

The traversal search of multi-dimensional parameter during the process of hypersonic target echo signal coherent integration,leads to the problem of large amounts of calculation and poor real-time performance.In view of these problems,a modified polynomial Radon-polynomial Fourier transform(MPRPFT)hypersonic target coherent integration detection algorithm based on Doppler feedback is proposed in this paper.Firstly,the Doppler estimation value of the target is obtained by using the target point information obtained by subsequent non-coherent integration detection.Then,the feedback adjustment of the coherent integration process is performed by using the acquired target Doppler estimation value.Finally,the coherent integration is completed after adjusting the search interval of compensation.The simulation results show that the algorithm can effectively reduce the computational complexity and improve the real-time performance on the basis of the effective coherent integration of hypersonic target echo signals.     

列控仿真系统中应答器的定位查找算法研究

在CTCS-3级列控系统的仿真平台中,应答器作为关键的地面设备,需要给车载等地面设备提供定位信息和线路信息等,以保证列车的正常安全行驶,所以在正确的位置给车载设备发送应答器报文信息是很重要的。提出了一种仿真平台中减小应答器定位查找误差的算法,阐述了该算法的实现过程。仿真结果表明该算法减小了应答器定位查找的误差,是仿真中保证列车正常安全行驶的一种重要算法。

Abstract：

In the simulation platform of CTCS-3 system,the balise is the indispensable above-ground equipment which sends the localization information and the line information to the on-board equipment to guarantee traffic safety.It is very important to send the balise text in the correct position and opportunity.An algorithm was developed to reduce the localization search error when a balise was found in the simulation platform and this algorithm’s realizing process in the simulation platform was elaborated on.The result of the simulation indicates this algorithm can reduce the localization search error for balises,which is important in guaranteeing the normal and safe operation for trains.     

Joint TDOA and AOA location algorithm

For the joint time difference of arrival(TDOA) and angle of arrival(AOA) location scene,two methods are proposed based on the rectangular coordinates and the polar coordinates,respectively.The problem is solved perfectly by calculating the target position with the joint TDOA and AOA location.On the condition of rectangular coordinates,first of all,it figures out the radial range between target and reference stations,then calculates the location of the target.In the case of polar coordinates,first of all,it figures out the azimuth between target and reference stations,then figures out the radial range between target and reference stations,finally obtains the location of the target.Simultaneously,simulation analyses show that the theoretical analysis is correct,and the proposed methods also provide the application of the joint TDOA and AOA location algorithm with the theoretical basis.     

Radar emitter signal recognition method based on improved collaborative semi-supervised learning

Rare labeled data are difficult to recognize by using conventional methods in the process of radar emitter recognition. To solve this problem, an optimized cooperative semisupervised learning radar emitter recognition method based on a small amount of labeled data is developed. First, a small amount of labeled data are randomly sampled by using the bootstrap method, loss functions for three common deep learning networks are improved, the uniform distribution and cross-entropy function are combin...     

Nonlinear RCMC method for spaceborne/airborne forward-looking bistatic SAR

In the spaceborne/airborne forward-looking bistatic synthetic aperture radar (SA-FBSAR),due to the system platforms’ remarkable velocity difference and the forward-looking mode,the range cell migration (RCM) not only depends on the target’s twodimensional location,but also varies with the range location nonlinearly.And the nonlinearity is not just the slight deviation from the linear part,but exhibits evident nonlinear departure in the RCM trajectory.If the RCM is not properly corrected,nonlinear image distortions would occur.Based on the RCM model,a modified two-step RCM compensation (RCMC) method for SA-FBSAR is proposed.In this method,firstly the azimuth-dependent RCM is compensated by the scaling Fourier transform and the phase multiplication.And then the range-dependent RCM is removed through interpolation.The effectiveness of the proposed RCMC method is verified by the simulation results of both point scatterers and area targets.     

基于约束的单舰纯方位跟踪算法

提出一种把运动目标舰艇的航速约束以及对陆地岛礁规避的约束加入修正增益推广卡尔曼滤波器的方法 ,对目标观测方程和目标状态方程分别进行修正 ,用于单舰对海上运动舰艇辐射源进行纯方位跟踪。航速约束可以当作输出为 0的增加的观测数据来处理 ;另外 ,根据当前估计的目标位置和航速 ,当下一个周期目标将航行到陆地岛礁或即将航行到陆地岛礁时 ,用规避因子矩阵来修正目标舰的航向和航速 ,以避免目标航行到陆地岛礁。计算机模拟结果表明 ,该方法能提高对海上运动舰艇辐射源的无源定位精度。     

基于航速修正处理的单舰被动定位算法

提出一种基于航速修正处理的单舰被动定位算法，在修正增益推广卡尔曼滤波器的基础上，该算法把运动目标舰艇的航道约束当作输出为0的增加的观测数据加入到测量方程，约束的强度由约束条件的噪声方差确定。提出一种规避因子，用来约束目标状态方程中的航速，基本思想是根据当前估计的目标位置和航速，估计了一个针航行到陆地岛礁或即将航行到陆地岛礁时，用规避因子矩阵来修正航速的方向和大小，避免了出现目标航行到陆地岛礁的情况。计算机模拟结果表明，航速修正处理后不会出现穿越陆地岛礁的运动舰艇航透，同时还能提高对海上运动舰艇辐射源的被动定位精度。     

自适应推广Kalman滤波应用于水下被动目标定位

针对在被动方式下进行水下目标定位容易出现滤波发散、收敛速度慢以及精度不高等问题,研究了一种修正极坐标系下的自适应推广卡尔曼滤波算法。它能够在线估计虚拟系统噪声的统计特性,从而消除了动态模型线性化误差带来的不良影响。仿真结果表明,该算法在收敛速度、估计精度以及稳定性方面都优于常规的卡尔曼滤波器。     

利用相位变化率对固定辐射源的无源被动定位

无源被动定位是利用从威胁辐射源接收到的辐射信息,对威胁辐射源进行定位的技术。以往的研究,常常局限于利用方向角（ＤＯＡ）信息。由于定位精度对角度测量误差的敏感性,仅利用ＤＯＡ信息很难得到迅速准确的位置信息。本文提出了一种利用相位变化率信息进行快速定位的定位方法,并给出了相应的算法和仿真结果,以及与传统只测角定位法的比较。     

基于目标之间拓扑信息的数据关联方法

数据关联是多平台多源信息融合系统中的关键问题。当传感器平台高速移动时,其自身的定姿定位往往存在一定误差,此时多个传感器对同一目标形成的量测经过坐标转换到同一坐标系下后会存在很大偏差,通过目标位置、速度等信息进行关联难度较大。所以,尝试提取目标的另一特征—目标之间的拓扑信息,通过对目标之间的拓扑信息进行模糊匹配和搜索,找到最佳的关联拓扑组,为数据关联和配准提供进一步校准的先验信息。仿真实验表明该方法具有较高的关联精度和鲁棒性。     

异类传感器系统目标快速定位方法

在异类传感器系统中,快速、准确地定位技术对于数据的关联、目标的跟踪至关重要。为解决异类传感器系统中目标定位问题,提出了快速目标定位法。该方法首先将不完整的测量补充为完整测量,然后用精度加权法实现多测量之间的融合得到目标的位置估计,为提高估计的精度,最后采用扩展加权最小二乘法进行目标位置的二次估计。仿真实验结果表明,提出的目标定位方法是一种快速、有效的目标定位方法,定位误差的方差接近Cramer-Rao下界。     

结合聚类的GM-PHD滤波器辐射源群目标跟踪

群目标跟踪是一种情况更为复杂的多目标跟踪问题,由于军事辐射源目标经常出现雷达关机的情况,因此常用的多目标跟踪方法对于这类辐射源群目标的跟踪效果并不理想。为此,结合聚类技术提出了一种改进的高斯混合概率假设密度(Gaussian mixture probability hypothesis density,GM-PHD)滤波器跟踪方法。该方法在GM-PHD滤波器的更新过程中,通过引入群中心产生的虚拟量测信息以提高目标跟踪性能,但不进行量测集划分。获得单一个体目标的估计状态后利用Jensen-Shannon divergence计算其相似度,然后再对估计目标进行聚类以实现群目标的跟踪。最后通过对相邻时刻的群中心轨迹点进行关联匹配,从而获得群目标的完整运动轨迹。仿真实验结果表明,所提方法能够对辐射源群目标进行有效跟踪,并具有较好的目标跟踪性能。     

基于相位差变化率测量的单站定位方法

利用观测平台相对目标辐射源的运动信息,在测角基础上增加相位差变化率信息可实现对目标被动定位,但该定位方法通过相位差法测角,需要增加设备以解相位模糊.针对上述不足,提出一种三角基线只测相位差变化率的定位方法,该方法通过测量两组相位差变化率解得方位角,避免了解模糊运算.给出了测角误差、定位误差表述式,通过仿真分析了相位差变化率对测角精度、定位精度的影响.     

基于TDOA的无人机集群协同单目标定位

无源定位作为现代信息化战场中电子侦察的重要技术, 可以在自身不辐射电磁波的情况下实现对敌方目标的精确定位。以高灵活性、高安全性的无人机(unmanned aerial vehicle, UAV)集群为接收站, 研究基于到达时差测量的辐射源定位方法。作为高机动平台, UAV集群的位置误差更大, 基于该情况对Chan算法、Taylor算法进行改进, 并提出了一种粒子群泰勒协同的解算方法。与其他方法的定位结果进行对比, 仿真结果表明所提的方法定位精度接近克拉美罗下界(Cramer-Rao lower bound, CRLB), 解决了Taylor算法的初值问题。     

基于规则的无人机编队队形构建与重构控制方法

针对已有方法在无人机编队队形控制方面的不足,结合无人机系统有限范围感知的特点提出一种基于规则的队形控制方法。首先,利用目标位置选择算法为编队成员选择刚体中的期望位置点,使分布式条件下的复杂无人机编队队形控制问题转化为个体对自身期望位置点的追踪问题;其次,通过控制协议的设计引导编队成员对自身的期望位置点进行追踪和避免碰撞;最后,在netlogo平台上实现了队形的控制;进一步,将目标位置选择算法与基于全局信息的“禁忌搜索”优化算法的效果进行了对比。实验表明:本文的控制方法简单,生成的航迹图简洁、平滑,其效果与基于全局信息的优化效果接近,且可生成任意队形和对突发威胁能主动有效的规避。