2020 IEEE/ION Position, Location and Navigation Symposium (PLANS)最新文献_第6页

High-Resolution Correlator Based Detection of GPS Spoofing Attacks Using the LASSO 基于高分辨率相关器的LASSO GPS欺骗攻击检测

2020 IEEE/ION Position, Location and Navigation Symposium (PLANS) Pub Date : 2020-04-01 DOI: 10.1109/PLANS46316.2020.9109959

Erick Schmidt, Nikolaos Gatsis, D. Akopian

{"title":"High-Resolution Correlator Based Detection of GPS Spoofing Attacks Using the LASSO","authors":"Erick Schmidt, Nikolaos Gatsis, D. Akopian","doi":"10.1109/PLANS46316.2020.9109959","DOIUrl":"https://doi.org/10.1109/PLANS46316.2020.9109959","url":null,"abstract":"This work proposes a novel sparsity-based decomposition method for the correlator output signals in GPS receivers capable of detecting spoofing attacks. We model complex correlator outputs of the received signal to form a dictionary of triangle-shaped replicas and employ a sparsity technique that selects potential matching triangle replicas from said dictionary. We formulate an optimization problem at the receiver correlator domain by using the Least Absolute Shrinkage and Selection Operator (LASSO) to find sparse code-phase peaks where such triangle-shaped delays are located. The optimal solution of this optimization technique discriminates two different code-phase values as authentic and spoofed peaks in a sparse vector output. We use a threshold to mitigate false alarms. Additionally, we present an expansion of the model by enhancing the dictionary to a collection of shifted triangles with higher resolution. Our experiments are able to discriminate authentic and spoofer peaks from synthetic GPS-like simulations. We also test our method on a real dataset, namely the Texas Spoofing Test Battery (TEXBAT). Our method achieves less than 1% detection error rate (DER) in nominal signal-to-noise ratio (SNR) conditions.","PeriodicalId":273568,"journal":{"name":"2020 IEEE/ION Position, Location and Navigation Symposium (PLANS)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131612871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Intercepting Unmanned Aerial Vehicle Swarms with Neural- Network-Aided Game-Theoretic Target Assignment 基于神经网络辅助博弈论目标分配的无人机群拦截

2020 IEEE/ION Position, Location and Navigation Symposium (PLANS) Pub Date : 2020-04-01 DOI: 10.1109/PLANS46316.2020.9110234

Nicholas G. Montalbano, T. Humphreys

引用次数: 2

Overbounding GNSS/INS Integration with Uncertain GNSS Gauss-Markov Error Parameters GNSS高斯-马尔可夫误差参数不确定的GNSS/INS超边界集成

2020 IEEE/ION Position, Location and Navigation Symposium (PLANS) Pub Date : 2020-04-01 DOI: 10.1109/PLANS46316.2020.9109874

Omar García Crespillo, M. Joerger, S. Langel

引用次数: 8

An End-to-End Process for Local Space Situational Awareness from Optical Observers 光学观测者对局部空间态势感知的端到端过程

2020 IEEE/ION Position, Location and Navigation Symposium (PLANS) Pub Date : 2020-04-01 DOI: 10.1109/PLANS46316.2020.9109868

D. Zuehlke, T. Henderson, T. A. Lovell, Alex Sizemore

引用次数: 5

Compact In-Run Navigation Grade IMU Based on Quartz MEMS 基于石英MEMS的紧凑型导航级IMU

2020 IEEE/ION Position, Location and Navigation Symposium (PLANS) Pub Date : 2020-04-01 DOI: 10.1109/PLANS46316.2020.9109851

S. Zotov, A. Srivastava, Ken Kwon, Jeremy Frank, Erwin Parco, Martin Williams, S. Shtigluz, Kenneth Lyons, M. Frazee, D. Hoyh, A. Lu

引用次数: 0

An UWB-based communication protocol design for an infrastructure-free cooperative navigation 基于uwb的无基础设施协同导航通信协议设计

2020 IEEE/ION Position, Location and Navigation Symposium (PLANS) Pub Date : 2020-04-01 DOI: 10.1109/PLANS46316.2020.9110154

Jianan Zhu, Solmaz S. Kia

引用次数: 2

On the calibration aspects of MEMS-IMUs used in micro UAVs for sensor orientation 微型无人机传感器定位用mems - imu的标定问题

2020 IEEE/ION Position, Location and Navigation Symposium (PLANS) Pub Date : 2020-04-01 DOI: 10.1109/PLANS46316.2020.9110160

P. Clausen, J. Skaloud

引用次数: 7

Deep Learning-Aided Spatial Discrimination for Multipath Mitigation 基于深度学习的多路径空间识别算法

2020 IEEE/ION Position, Location and Navigation Symposium (PLANS) Pub Date : 2020-04-01 DOI: 10.1109/PLANS46316.2020.9109935

Ali A. Abdallah, Z. Kassas

引用次数: 23

Design and Implementation of a Software Defined Radio GNSS Receiver Based on OpenCL 基于OpenCL的软件无线电GNSS接收机的设计与实现

2020 IEEE/ION Position, Location and Navigation Symposium (PLANS) Pub Date : 2020-04-01 DOI: 10.1109/PLANS46316.2020.9110191

Janos Buttgereit, T. Schwarte, G. Kappen

{"title":"Design and Implementation of a Software Defined Radio GNSS Receiver Based on OpenCL","authors":"Janos Buttgereit, T. Schwarte, G. Kappen","doi":"10.1109/PLANS46316.2020.9110191","DOIUrl":"https://doi.org/10.1109/PLANS46316.2020.9110191","url":null,"abstract":"During the design and implementation of digital circuits for various applications, mapping of algorithms to different hardware components is a central task to achieve best in class performance (e.g., low power consumption per position fix, position accuracy and position deviation for satellite navigation receivers). During the last decade software defined radio receivers (SDRs) and Field Programmable Gate Array (FPGA) based receivers gain more and more importance during the prototyping phase and for receivers with an expected low volume production. These receivers are also of special interest during the introduction of new signals and frequency bands. FPGA based receivers allow a flexible design and the implementation of highly parallel digital logic and software based processing at the same time. The fundamental drawback of FPGA based GNSS receiver solutions is the high design complexity and the enlarged design space. In this context the design space describes the number of parameters the designer has to consider, to optimize the final design for a given application. Successful navigation in this design space, requires experience in various disciplines (e.g. Radio Frequency (RF) engineering, signal processing, GNSS algorithm design). The main idea of this paper is to ease the design, simulation and cost optimization of Software Defined Radio (SDR) GNSS receivers, implemented on standard PCs, Graphical Processing Units (GPUs) and FPGAs. The idea is to describe the receiver architecture and the receiver specifications at a very high and thus understandable level. During the next step a compiler maps the different receiver signal processing blocks to the existing hardware (i.e. General Purpose Computer (GPC), FPGA or GPU). Using this approach, the most time consuming parts (i.e. design description and specification) have to be done only once and the design is based on a single code base.","PeriodicalId":273568,"journal":{"name":"2020 IEEE/ION Position, Location and Navigation Symposium (PLANS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125322353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Joint Train Localization and Track Identification based on Earth Magnetic Field Distortions 基于地磁场畸变的联合列车定位与轨道识别

2020 IEEE/ION Position, Location and Navigation Symposium (PLANS) Pub Date : 2020-04-01 DOI: 10.1109/PLANS46316.2020.9110149

B. Siebler, O. Heirich, S. Sand, U. Hanebeck

{"title":"Joint Train Localization and Track Identification based on Earth Magnetic Field Distortions","authors":"B. Siebler, O. Heirich, S. Sand, U. Hanebeck","doi":"10.1109/PLANS46316.2020.9110149","DOIUrl":"https://doi.org/10.1109/PLANS46316.2020.9110149","url":null,"abstract":"In this paper a train localization method is proposed that uses local variations of the earth magnetic field to determine the topological position of a train in a track network. The approach requires a magnetometer triad, an accelerometer, and a map of the magnetic field along the railway tracks. The estimated topological position comprises the along-track position that defines the position of the train within a certain track and the track ID that specifies the track the train is driving on. The along-track position is estimated by a a recursive Bayesian filter and the track ID is found from a hypothesis test. In particular the use of multiple particle filter, each estimating the position on different track hypothesis, is proposed. Whenever the estimated train position crosses a switch, a particle filter for each possible track is created. With the position estimates of the different filters, the likelihood for each track hypothesis is calculated from the measured magnetic field and the expected magnetic field in the map. A comparison of the likelihoods is subsequently used to decide which track is the most likely. After a decision for a track is made, the unnecessary filters are deleted. The feasibility of the proposed localization method is evaluated with measurement data recorded on a regional train. In the evaluation, the localization method was running in real time and overall an RMSE below five meter could be achieved and all tracks were correctly identified.","PeriodicalId":273568,"journal":{"name":"2020 IEEE/ION Position, Location and Navigation Symposium (PLANS)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117237722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10