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localization-kalman-filter

robot localization by kalman filter

maast

MATLAB Algorithm Availability Simulation Tool

multiple-modal-adaptive-estimation-using-boolean-kalman-filter

The inference of Boolean gene regulatory networks observed through noise is concern of this package. The algorithm is based on the optimal MMSE state estimator for a Boolean dynamical system, known as the Boolean Kalman Filter (BKF). In the presence of partial knowledge about the network, a bank of BKFs representing the candidate models is run in parallel in a Bayesian framework known as a multiple model adaptive estimation (MMAE). Reference: Imani, Mahdi, and Ulisses Braga-Neto. "Optimal gene regulatory network inference using the Boolean Kalman filter and multiple model adaptive estimation." 2015 49th Asilomar Conference on Signals, Systems and Computers. IEEE, 2015.

nju_beidou

北斗项目代码，软件以及硬件图

node-rtk

rtklib node js module

noise-cancellation-lms-adaptive-filter

This project implements an adaptive filter which cancels the noise from a corrupted signal using normalized least mean square algorithm.

noise-filters

noise_filters

noise_reducers

Some LIDAR filters.

noisefiltersr

This is a modified copy of the NoiseFiltersR package which should run significantly faster for many algorithms. I take no credit for the algorithms themselves or the implementation - I just sped a few things up.

novatel_gps_driver

ROS driver for NovAtel GPS / GNSS receivers

piksi_tools

Tools for the Piksi GNSS receiver.

pirtk

RTKLIB for the Raspberry Pi

ppp-tools

Scripts for GPS-Precise Point Positioning based on RINEX files

predicting-transportation-modes-of-gps-trajectories

Understanding transportation mode from GPS (Global Positioning System) traces is an essential topic in the data mobility domain. In this paper, a framework is proposed to predict transportation modes. This framework follows a sequence of five steps: (i) data preparation, where GPS points are grouped in trajectory samples; (ii) point features generation; (iii) trajectory features extraction; (iv) noise removal; (v) normalization. We show that the extraction of the new point features: bearing rate, the rate of rate of change of the bearing rate and the global and local trajectory features, like medians and percentiles enables many classifiers to achieve high accuracy (96.5%) and f1 (96.3%) scores. We also show that the noise removal task affects the performance of all the models tested. Finally, the empirical tests where we compare this work against state-of-art transportation mode prediction strategies show that our framework is competitive and outperforms most of them.

presentations

Repository with my presentations on conferences

qt_rtklib_fix

准备调试RTKLIB界面版本，熟悉算法，改界面

quadspp

Multi-GNSS Standard Point Positioning

reachview

Reach-hosted web-interface for RTKLIB

recursive-kalman-filter

Simple recursive Kalman filter for predicting Gaussian white noise time series

robust-kalman

Robust Kalman filter with adaptive noise statistics estimation.

robustgnss

Robust GNSS Processing With Factor Graphs

rpi-gps-tracker

A GNSS (GPS, GLONASS, BeiDou, etc.) reciever, recorder, and cellular/radio transponder to be run on a mobile Raspberry Pi Zero.

rssi-geolocation

RSSI-based smartphone geolocation using flying robots

rtcm3

System for Parseing RTCM3.x packets

rtk-str2str

str2str app of RTKLIB 2.4.3beta, reorgnized files to be compiled by CMake

rtk-streamserver

Modified from str2str, a CUI AP of RTKLIB 2.4.2. The strsvrstat loop in the main function was modified by ddding some code to update the system time. Thus every time when the strsvrstat ( show stream server status ) executed, the GPS time in the GPS raw message will be extracted and be utilized to update the system time. If the difference between GPS time and system time is not big ( er than 1sec ), the system time will not update.

rtkchip

CHIP rtklib integration

rtkgps

Playing with rtklib on android

rtklib