kalmanjs | Javascript based Kalman filter for 1D data | Widget library

by wouterbulten Java Version: 1.1.0 License: MIT

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | kalmanjs Summary

kalmanjs is a Java library typically used in User Interface, Widget applications. kalmanjs has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However kalmanjs build file is not available. You can install using 'npm i kalmanjs' or download it from GitHub, npm.

Javascript based Kalman filter for 1D data. Sometimes you need a simple noise filter without any dependencies; for those cases KalmanJS is perfect.

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Quality

Security

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Support

kalmanjs has a low active ecosystem.

It has 315 star(s) with 66 fork(s). There are 12 watchers for this library.

It had no major release in the last 12 months.

There are 1 open issues and 9 have been closed. On average issues are closed in 67 days. There are 5 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of kalmanjs is 1.1.0

Quality

kalmanjs has no bugs reported.

Security

kalmanjs has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

kalmanjs is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

kalmanjs releases are available to install and integrate.

Deployable package is available in npm.

kalmanjs has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions, examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi has reviewed kalmanjs and discovered the below as its top functions. This is intended to give you an instant insight into kalmanjs implemented functionality, and help decide if they suit your requirements.

Filters a measurement value
Filter a measurement

Get all kandi verified functions for this library.

kalmanjs Key Features

No Key Features are available at this moment for kalmanjs.

kalmanjs Examples and Code Snippets

No Code Snippets are available at this moment for kalmanjs.

Community Discussions

Trending Discussions on kalmanjs

Node.js kalman filter 1D

QUESTION

Node.js kalman filter 1D

Asked 2019-Feb-22 at 00:50

First of all, Hello I am working on node.js javascript on interior positioning with Ibeacon. As a helper in my work: I use Evothings Studio. I'm transferring my codes to Evothings studio and viewing my work from my android and ios mobile phone. Now I want to tell you the problem I've had. According to RSSI Signal level, I find the distance is not very accurate in the calculations. I want to use Kalman Filter to clear the noises of this signal level (RSSI). This article describes the use of the kalman filter in Javascript. It is said to be easy to implement but I could not start practicing. "" Kalman Filter library: "https://github.com/wouterbulten/kalmanjs". How do I clear the noise from RSSI signals with this kalman filter? How do I apply the Kalman filter to these codes?

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ANSWER

Answered 2019-Feb-22 at 00:50

After you complete experimenting with a Kalman Filter, you will likely find that the error in your distance estimates is still too high. This is because of the other sources of error besides random noise in your RSSI measurement, many of which can be a function of other variables (e.g. reflection, obstruction, antenna pattern variations) that affect the radio signal level as measured by the receiver.

In general, using direct distance calculations based on RSSI is at best accurate enough to estimate 0.5-2 meters at a true distance of 1 meter, and much lower accuracy at greater distances. This is true even after filtering out noise with a Kalman filter or running average. (Note iOS distance estimates use a 20 second running average on RSSI and RSSI field values on CLBeacon are averaged over one second.)

If using trilateration or similar approaches to calculate position, you will find that you can only get workable results at very short distances of no more than 1-2 meters.

Source https://stackoverflow.com/questions/54817228

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install kalmanjs

The KalmanJS library is a small javascript library and can easily be integrated in to your project manually. Alternatively, the library can be included using npm.

Support

Please see the blog post (KalmanJS, Lightweight Javascript Library for Noise filtering) for more information about using this library. Any questions can be posted there as comments.

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