A Terrain Referenced UAV Localization Algorithm Using Binary Search Method

This study focuses on localization of Unmanned Aerial Vehicles (UAV) since permanent navigation has vital significance to support position information and to avoid getting lost. Actually, there exist effective aeronautical navigation systems in use. Inertial Navigation System (INS) and Global Positioning System (GPS) are two representatives of the most common systems utilized in traditional aerial vehicles. However, an alternative supporter system for UAVs should be mentioned since INS and GPS have serious deficiencies for UAVs such as accumulated errors and satellite signal loss, respectively. Such handicaps are coped with integrating these systems or exploiting other localization systems. Terrain Referenced Navigation (TRN) could be a good alternative as a supporter mechanism for these main systems. This study aims to localize a UAV accurately by using only the elevation data of the territory in order to simulate a TRN system. Application of the methodology on a real UAV is also considered for the future. Thus assumptions and limitations are designed regarding the constraints of real systems. In order to represent terrain data, Digital Elevation Model (DEM) with original 30 meter-resolution (Eroglu and Yilmaz 2013) and also synthetically generated 10 meter-resolution maps are utilized. The proposed method is based on searching the measured elevation values of the flight within the DEM and makes use of simulation techniques to test the accuracy and the performance. The whole system uses sequences of elevation values with a predefined length (i.e. profile). Mainly, all possible profiles are generated and stored before the flight. We identify, classify and sort profiles to perform search operations in a small subset of the terrain. During the flight, a measured flight profile is searched by the Binary search method (Eroglu 2013) within a small neighborhood of corresponding profile set.     

一种新的复合地形辅助导航方法

地形辅助导航方法中,并行Kalman滤波和关联算子都使用雷达阵列测量的地形高度与地形高程数据对比得到飞行器当前定位.并行Kalman滤波中虽然采用了多模式自适应技术(Multi Mode Adaptive Estimation,MMAE),仍然难以确保系统在遇到地形突变情况时的性能.关联算子技术基于贝叶斯原理,计算简单,并且具有较好的鲁棒性.基于两种方法,提出一种复合地形导航系统,使用关联算子监视并行Kalman滤波,保证定位精度的鲁棒性.实验使用真实地形数据验证了该方法的有效性.     

Moment Matched Gaussian Kernel and Region Representative Likelihood for Performance Improvement of PMF-based TRN

This paper proposes two techniques to improve the performance of Point Mass Filter (PMF) based Terrain Referenced Navigation (TRN). The first is the kernel     

基于激光雷达地形测绘建立DEM模型

地形测绘技术在地理信息系统及地形辅助导航中起着相当重要的作用,当前地形测绘技术已由过去的人工测绘发展为利用多种手段进行自动测绘。其中利用机载或星载激光雷达进行测绘是一种先进的测绘手段,目前在国际上已普遍采用。该方法与传统的人工测绘比较,具有全天候、精确性高、实时性强等诸多优点。主要介绍了利用机载激光雷达并结合全球卫星定位系统、惯性导航技术建立地形高程模型的一种新方法。该方法在带状地形的测量方面具有较好的精度和效果。     

基于地形熵和地形差异熵的综合地形匹配算法

水下运载体的导航主要以惯性导航为主，但是，由于水下运载体在海底的运行速度比较慢，惯性导航系统随着时间的累积出现了定位误差增大的缺点，因此需要地形辅助导航来纠正惯导的误差。文中将地形熵和地形差异熵的概念引入到水下地形匹配算法中，设计了基于地形熵和地形差异熵的综合地形匹配算法，并将该算法应用于水下地形辅助导航系统中，经验证该算法取得了良好的纠正惯导定位的效果，实现了水下地形辅助导航的任务。     

基于雷达高度计-星敏感器的卫星自主导航精度分析

考虑到采用多个雷达高度计进行卫星自主定位的不足,提出采用单个雷达高度计,结合星敏感器提供的测量信息,构成雷达高度计—星敏感器的卫星组合自主导航系统。通过大量的仿真实验,分析了地形起伏、可见导航星数目、星敏感器精度、地平仪精度等因素对定位精度的影响,并总结其变化规律,对提高卫星自主定位精度有重要的借鉴意义。     

A shadow detection and extraction algorithm using digital elevation models and x‐band weather radar measurements

The aviation industry has been investigating the potential of synthetic and enhanced vision systems (SVS and EVS) to increase the situational awareness of pilots who are operating in low‐visibility weather conditions. Synthetic vision displays provide a real‐time depiction of a terrain model from the pilot's perspective. To ensure the integrity of this terrain depiction, consistency checking using remote sensing of the terrain environment has been suggested. This requires the detection and extraction of terrain features from both the model and the sensor measurements. Further, the features must be represented in the same reference domain.

Terrain shadowing occurs when areas are not in the line‐of‐sight of the observer. It is these shadowed regions and their morphological characteristics that are identified as the feature domain in which consistency can be assessed between two sources of terrain information. This paper describes an algorithm to extract shadow features from digital elevation models during flight to enable direct comparison with x‐band radar modus operandi. Results are presented using flight‐test data acquired from two platforms with different radar equipment.

The proposed algorithm not only has application to the consistency‐checking problem, but also to terrain navigation, image fusion, and digital elevation model accuracy assessments.     

低空突防导航实时仿真测试系统研究

为了低空飞行突破敌人防线,现代先进飞机配有低空突防导航设备导引飞行员实现贴地飞行和低空障碍回避;然而,低空突防导航设备的试飞试验不仅风险极高,而且代价高昂、试验周期长;文中构建了低空突防导航实时仿真测试系统,给出了仿真测试系统的结构设计、关键技术设计,并基于此系统对突防导航算法进行充分仿真测试,大大减少了实际试飞验证的次数,从而降低了试飞风险和试飞成本。     

地形对雷达高度计卫星自主导航精度影响分析

以中低轨道卫星为应用背景,对基于星载雷达高度计的卫星自主导航系统展开研究,着重分析了雷达高度计卫星自主导航中的关键因素,即地形起伏对导航精度的影响。根据实际地形的统计特性,并结合导航精度仿真分析的需要,建立了模拟地形的数学模型;对不同地形条件下雷达高度计卫星自主导航系统的导航精度进行了仿真研究,分析了不同的地形条件对雷达高度计卫星自主导航精度的影响。研究的结论对雷达高度计自主导航技术的实际应用将具有重要的参考价值。     

Simultaneous calibration and navigation (SCAN) of multiple ultrasonic local positioning systems

This paper proposes a Simultaneous Calibration and Navigation (SCAN) algorithm of a multiple Ultrasonic Local Positioning Systems (ULPSs) that cover an extensive indoor area. The idea is the development of the same concept than SLAM (Simultaneous Localization and Mapping), in which a Mobile Robot (MR) estimates the map while it is navigating. In our approach, the MR calibrates the beacons of several ULPSs while it is moving inside the localization area. The concept of calibration is the estimation of the position of the beacons referenced to a known map. The scenario is composed of some calibrated ULPSs that we denote as Globally Referenced Ultrasonic Local Positioning Systems (GRULPSs) that are located in strategic points like entrances covering the start and the end of a possible trajectory in the environment. Additionally, there are several non-calibrated ULPSs named Locally Referenced Ultrasonic Local Positioning Systems (LRULPSs) that are placed around the localization area. The proposal uses a MR with odometer for calibrating the beacons of the LRULPSs while it is navigating on their coverage area and go from one GRULPS to another. The algorithm is based on multiple filters running in parallel (one filter for each LRULPS and another one for the GRULPSs) that estimate the global and local trajectories of the MR (one trajectory for each local reference system of the LRULPSs) fusing the information related to the Ultrasound Signals (US) and the odometer of the MR. The position of the beacons of the LRULPSs are obtained by a transformation vector for each LRULPS that converts the local coordinates to the global reference system. This transformation vector is calculated using several points of a local trajectory and the corresponding points of the global one. The method is independent of the type of filter, provided that it works properly with non-linear systems and possibly non-Gaussian noise. Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF) and H-∞ Filter have been tested, in simulations and real experiments, in order to compare their performance in this case.     

几种地形辅助导航方法的比较

地形辅助导航系统将飞行航迹下的地形高度信息与机载数字高程地图比较后得到导航定位结果，并以此对惯性导航主系统进行必要的修正。针对基于扩展Kalman滤波，基于关联算子和基于点群滤波的3种地形辅助导航方法，介绍其基本原理后。采用真实地形数据进行仿真，比较不同飞行情况下这些方法的性能。     

Map‐aided localization in sparse global positioning system environments using vision and particle filtering

A map‐aided localization approach using vision, inertial sensors when available, and a particle filter is proposed and empirically evaluated. The approach, termed PosteriorPose, uses a Bayesian particle filter to augment global positioning system (GPS) and inertial navigation solutions with vision‐based measurements of nearby lanes and stop lines referenced against a known map of environmental features. These map‐relative measurements are shown to improve the quality of the navigation solution when GPS is available, and they are shown to keep the navigation solution converged in extended GPS blackouts. Measurements are incorporated with careful hypothesis testing and error modeling to account for non‐Gaussian and multimodal errors committed by GPS and vision‐based detection algorithms. Using a set of data collected with Cornell's autonomous car, including a measure of truth via a high‐precision differential corrections service, an experimental investigation of important design elements of the PosteriorPose estimator is conducted. The algorithm is shown to statistically outperform a tightly coupled GPS/inertial navigation solution both in full GPS coverage and in extended GPS blackouts. Statistical performance is also studied as a function of road type, filter likelihood models, bias models, and filter integrity tests. © 2011 Wiley Periodicals, Inc.     

信息融合技术在INS/GPS/TAN/SMN四组合系统中的应用

主要介绍了组合导航系统中多传感器信息融合技术的国内外发展状况,对INS/GPS/T AN/SMN(惯性系统/卫星导航系统/地形辅助导航/景象匹配导航)组合系统中的多传感器信息 融合的层次结构与融合方法,首次提出INS/GPS/TAN/SMN组合导航系统信息融合的层次结构 ,并提出了多源图像融合制导的思想与方法．本文指出比较有应用前景的信息融合研究方法 是基于模糊逻辑、小波分析、神经网络等人工智能的新方法,以及这些新方法与传统的随机 类方法相结合的随机 人工智能的信息融合方法．     

基于Hausdorff距离的海底地形匹配算法仿真研究

地形匹配算法是海底地形辅助导航系统的关键技术之一。根据海底地形的特殊特性，传统地形匹配算法直接应用于STAN时，易出现定位精度大幅降低和算法不稳定性问题。该文提出一种基于地形轮廓匹配原理的新算法，该算法利用改进的Hausdorff距离作为水深实时测量曲线与海底地形图水深曲线之间的度量函数。改进的Hausdorff距离对匹配对象存在的小误差不敏感，在一定程度上还可反映空间两条曲线的方位关系，该算法定位精度高、稳定性好。利用某海域地形图进行的仿真实验表明：该算法是可行的，定位精度比现有算法提高一倍左右。     

雷达对低空目标探测的地形遮蔽算法研究

地形遮蔽是影响雷达探测发现目标能力的关键因素.有效算法是实施模拟仿真的基础.在借鉴离散判断法思想的基础上,针对某实际问题,建立了雷达对低空目标探测的地形遮蔽模型算法.本算法实用性好、精度高,可用于作战推演的实时仿真.     

基于改进RBPF算法的轮式机器人SLAM导航系统设计

传统的机器人导航系统在复杂的地形环境中常常无法引导机器人躲避突然出现的障碍物,无法精准采集数据。为此提出一种改进RBPF算法的轮式机器人SLAM导航系统,对系统硬件和软件进行设计。系统硬件主要由导航功能模块、底盘驱动模块、控制模块组成,利用RPLIDAR A1型激光测距雷达设计导航功能模块,并设计底盘驱动模块和控制模块。软件设计中,以改进RBPF算法为基础,设计了轮式机器人SLAM导航系统的实现程序,应用算法代入的方式加强了普通轮式机器人导航算法对粒子计算与卡尔曼滤波的敏感程度。实验结果表明,改进RBPF算法在避障和计算误差方面的优势,证明了该系统相比传统避障后的路径选择更便捷,导航错误出现率降低了30%左右。     

新的改进K均值粒子群算法在组合导航的应用

在捷联惯导/卫星导航（SINS/GNSS）紧组合导航系统的非线性非高斯高动态模型中,一般K均值粒子群优化（PSO）算法易出现粒子退化、滤波发散等问题。针对上述问题,提出一种融入权值修正的K均值粒子群滤波方法。通过观测SINS/GNSS紧组合导航系统的精度因子(GDOP),来修正粒子权值,从而修正每个K均值的聚类中心的权重,进而优化粒子;并结合SINS/GNSS紧组合导航系统模型进行了仿真分析。结果表明在非线性非高斯高动态的情况下,该改进算法有效地抑制了滤波发散,提高了精度。     

Super-resolution imaging based on the BeiDou B3 signal

ABSTRACT

Using global navigation satellites to construct bi-static synthetic aperture radar for imaging has been a major research hotspot in passive radar. However, the low range resolution of Global Navigation Satellite signal (GNSS) limits the quality of actual scene imaging. To increase the range resolution of the imaging, a super-resolution imaging method by mixing the back-projection (BP) algorithm with truncated singular value decomposition (TSVD) is proposed. This paper first introduces the BeiDou Navigation Satellite System (BDS) signal model for ground imaging, carries out the range compression and describes the BP algorithm. Subsequently, the super-resolution method is given and some simulation results are demonstrated. Two field experimental cases, including targets of trees and ferries, are then carried out. The experimental results demonstrate the effectiveness of the proposed method.     

AUV terrain-aided navigation using a Doppler velocity logger

This paper addresses the design and implementation of terrain-aided navigation (TAN) methods for small autonomous underwater vehicles (AUVs) that rely on standard navigation sensors and dispense with the need for dedicated sensors for terrain data acquisition. The research described focuses on the problem of TAN implementation in underwater scenarios characterized by smooth sea-bottom topography and very shallow water, where the terrain information available for navigation is scarce. The navigation algorithms and the data fusion methods whose tests are documented in the paper build upon and expand prior theoretical work published by the authors; the TAN solutions adopted exploit the terrain information and the navigation data acquired with an inexpensive Doppler velocity logger (DVL) and a standard motion reference unit, respectively. The position estimation methods analyzed include a bi-dimensional particle filter (PF) and a four-dimensional Rao-Blackwellized PF that was designed to estimate the unknown Doppler velocity measurement biases responsible for the unbound localization errors typically observed in dead-recknoning navigation. The positioning accuracy achieved with these filters is compared with the output of a novel method, also proposed in the paper, that mechanizes a complementary-like filter designed to fuse the output of a TAN estimator with the velocity measurements provided by a DVL. Experimental results obtained during field tests with an autonomous marine vehicle are reported and analyzed.     

地形跟随/地形回避实时仿真系统的设计与实现

为了验证低空突防系统中的地形跟随/地形回避关键技术,设计了一套分布式实时仿真系统。该系统由主控机、地形跟随/地形回避(TF/TA)计算机和视景演示计算机组成。TF/TA计算机采用先进的嵌入式实时操作系统VxWorks进行TF/TA飞行轨迹规划,实时地形匹配,以及模拟雷达的实时数据生成。该系统可以验证算法,模拟飞机在空中飞行的实际效果,为TF/TA系统的试飞验证提供必要准备。