CRAWDAD tools/analyze/location/loceva

Loceva - an evaluation tool for 802.11-based positioning systems.Loceva is an evaluation tool for 802.11-based positioning systems. Loceva uses trace files generated by Loctrace to evaluate different kinds of positioning algorithms. A large number of state-of-the-art positioning algorithms are supported by Loceva. Loceva contains a lot of filters and generators to set up different scenarios and enable emulation.Lastmodified :2007-12-05Dataname :tools/analyze/location/locevaFile :loceva-0.5.1.src.tar.gz, loceva-0.5.1.tar.gz, property.prop.txtReleasedate :2007-09-14Change :the initial version.References :king-tools The Loceva websiteWebsite :http://www.crawdad.org/tools/analyze/location/locevaKeyword :802.11 GPS location signal strengthLicense :This tool is released under the GNU General Public License. Please respect our work and abide the license.Output :See "usage" for details.Parameters :See "usage" for details.Usage :Loceva can be controlled by a so-called property file. In Java a property file contains key-value-pairs with a equals character as seperator. Most configurable values of Loceva are accessible by properties so that the same jar file can be used to emulate a wide range of different scenarios. You can download an example property file that can be used to play around with Loceva. After downloading and unpacking the jar archive Loceva can be run with the following command: java -cp loceva-0.5.1.jar:locutil1-0.5.1.jar:locutil2-0.5.2.jar org.pi4.loceva.Loceva -offline FILENAME -online FILENAME [-prop PROPERTY] FILENAME can be a trace file containing offline traces as well as online traces. Both parameters -offline and -online are required. The -prop parameter can be used optionally to define a property file.Algorithm :1. Overview Trace files generated by Loctrace are used by Loceva to evaluate different kinds of positioning algorithms. A large number of state-of-the-art positioning algorithms are supported by Loceva. Loceva contains a lot of filters and generators to set up different scenarios and enable emulation. 2. Management To make it easy to evaluate and compare algorithms currently under research, Loceva contains a management part that enables emulation in general and allows to easily select different kinds of scenarios. For this, Loceva utilizes trace files created with Loctrace to emulate a specific scenario. Such an emulated scenario can then be used for a comparison of different positioning algorithms. This makes sure that differences in the results are based on the positioning algorithms and not on the environment that changed over time in a way beneficially for one particular algorithm. The creation and management of various scenarios is enabled by so-called filters. Filters create different scenarios by disabling or selecting different objects of a trace file. For instance, a MAC filter artificially switches off access points even if they have been part of the trace file. Another example is the position filter that disables different reference points of the fingerprint database based on their coordinates. 3. Algorithms The positioning part contains various positioning algorithms to make it easy to compare newly envisioned algorithms with state-of-the-art ones. The following list shows the positioning algorithms that are part of Loceva. The list is grouped by the research projects that have invented them: - RADAR: Nearest neighbor(s) in signal space, k nearest neighbors in signal space - PlaceLab: K nearest neighbors p unknown, Ranking - Rice: Histogram, Gaussian - Horus: Horus Although the main focus of Loceva is on positioning algorithms, it also contains a few continuous user tracking algorithms: - RADAR: Viterbi-like algorithm - Rice: Tracking - Horus: Horus 4. Analysis After selecting a certain scenario and positioning algorithm, Loceva computes the position error that would have occurred in this setting. The position error is defined as the Euclidean distance between the actual position of the user and the position estimate calculated by the algorithm. At the end of each emulation the average position error is printed, and a graph showing a cumulative distribution function of the position error (as shown in the figure below) is generated. Such a graph can be used to compare the position accuracy of different positioning algorithms by determining the median, 95th percentile and so on. Additionally, Loceva can be enabled to create a file that contains a log of intermediate results computed by the selected positioning algorithm. This log can be used with Locana to analyze the behavior of the positioning algorithm in question.

Loceva——一款基于802.11定位系统的评估工具。Loceva是一款专门针对802.11定位系统的评估工具。该工具通过分析由Loctrace生成的追踪文件，对各类定位算法进行评估。Loceva支持众多前沿的定位算法。它内置了大量的过滤器与生成器，用以构建多样化的场景并实现仿真模拟。最后修改日期：2007-12-05，数据集名称：tools/analyze/location/loceva，文件：loceva-0.5.1.src.tar.gz, loceva-0.5.1.tar.gz, property.prop.txt，发布日期：2007-09-14，变更：初始版本，参考文献：king-tools，Loceva网站：http://www.crawdad.org/tools/analyze/location/loceva，关键词：802.11 GPS 定位信号强度，许可证：本工具遵循GNU通用公共许可证发布。敬请尊重我们的劳动成果，并遵守许可证规定。输出：详见“使用说明”，参数：详见“使用说明”，使用说明：Loceva可通过所谓的属性文件进行控制。在Java中，属性文件包含以等号分隔的键值对。Loceva的大部分可配置值均可通过属性进行访问，从而使得相同的jar文件能够模拟多种不同的场景。您可以下载一个示例属性文件，用于探索Loceva的功能。下载并解压jar归档文件后，可以通过以下命令运行Loceva：java -cp loceva-0.5.1.jar:locutil1-0.5.1.jar:locutil2-0.5.2.jar org.pi4.loceva.Loceva -offline FILENAME -online FILENAME [-prop PROPERTY] 其中，FILENAME可以是包含离线追踪和在线追踪的追踪文件。参数-offline和-online均为必需参数。可选的参数-prop可用于定义属性文件。算法：1. 概述：Loceva利用Loctrace生成的追踪文件评估各类定位算法，支持众多前沿的定位算法。Loceva内置了大量的过滤器与生成器，用以构建多样化的场景并实现仿真模拟。2. 管理功能：为了便于评估和比较当前研究中的算法，Loceva包含一个管理部分，该部分允许一般性的仿真模拟，并能够轻松选择不同类型的场景。为此，Loceva利用Loctrace创建的追踪文件来模拟特定的场景。这样的模拟场景随后可用于不同定位算法的比较。这确保了结果差异是由定位算法引起的，而非环境随时间变化对某一特定算法有利。各种场景的创建与管理是通过所谓的过滤器实现的。过滤器通过禁用或选择追踪文件中的不同对象来创建不同的场景。例如，MAC过滤器会人为地关闭即使它们是追踪文件一部分的接入点。另一个例子是位置过滤器，它根据指纹数据库中参考点的坐标禁用不同的参考点。3. 算法：定位部分包含多种定位算法，便于比较新构思的算法与前沿算法。以下列表展示了Loceva中包含的定位算法，列表按发明它们的科研项目分组：- RADAR：信号空间中的最近邻（多个最近邻），信号空间中的k个最近邻- PlaceLab：k个最近邻p未知，排名- Rice：直方图，高斯- Horus：Horus 虽然Loceva的主要关注点是定位算法，但它也包含了一些连续用户跟踪算法：- RADAR：维特比算法类似- Rice：跟踪- Horus：Horus 4. 分析：在选定特定场景和定位算法后，Loceva计算在此设置下可能发生的定位误差。定位误差定义为用户实际位置与算法计算出的位置估计之间的欧几里得距离。在每次仿真结束时，打印平均位置误差，并生成一个显示位置误差累积分布函数的图表（如图所示）。此类图表可用于通过确定中位数、95百分位数等来比较不同定位算法的位置精度。此外，Loceva还可启用创建一个包含所选定位算法计算出的中间结果的日志文件。此日志文件可用于与Locana一起分析所讨论定位算法的行为。