It is the set of tools for passive radio location. PLoc contains localization functions and the program for modeling the localization of a signal emitter. Read more.
PLoc has three directs localization methods:
- Direct;
- Quadratic Planar (QP);
- Rectangle;
and one approximate method:
- Elder-Mead.
In practice, Elder-Mead gives the best answers but requires too much time. So, you can calculate the answer by QP or Rectangle method and clarify the result by Elder-Mead.
Direct methods work with a certain number of detectors (three detectors in Direct and QP methods and four in Rectangle). But they can be scaled to a large number by localization for each locator's combination. In this way, we need to combine the results.
PLoc have five result combine methods:
- Mean;
- Filtered Mean (mean with discarding bursts);
- Median;
- Time Sum (give priority combination with minimal time detection);
- Triangle (only for Direct and QP, give priority more regular triangles).
In practice, Rectangle method gives the best results with Median combiner. For other methods don't have a favorite combiner.
PLoc has a program for the modeling localization process. With their help, you can choose the bests position for your detectors and method of localization. Read more about the program.
Also, you can use scripts that were written on Python for partly visualization of results.
Examples of localization are with added errors.
Field of mean distance errors. Localization by QP methods on plaint.
Spread of lighting localization with curce in the center of the triangle of stations.
Spread of time lighting's appearance with source in the center of the triangle of stations.
Field of mean distance errors. Localization by Elder-Mead on sphere.
