# JunshengFu/tracking-with-Extended-Kalman-Filter

<https://repo.masters-masters.com/en/repos/JunshengFu/tracking-with-Extended-Kalman-Filter>

[Home](https://repo.masters-masters.com/en) › [JunshengFu](https://repo.masters-masters.com/en/owners/JunshengFu) › [tracking-with-Extended-Kalman-Filter](https://repo.masters-masters.com/en/repos/JunshengFu/tracking-with-Extended-Kalman-Filter)

JunshengFu/tracking-with-Extended-Kalman-Filter has 835 stars on GitHub. Its RepoMasters card: Beta tier. Object (e.g Pedestrian, vehicles) tracking by…

| Field | Value |
| --- | --- |
| Owner | [JunshengFu](https://repo.masters-masters.com/en/owners/JunshengFu) |
| Stars | 835 |
| Forks | 266 |
| Language | [C++](https://repo.masters-masters.com/en/languages/c-plus-plus) |
| License | MIT |
| Created | 2017 |
| Topics | extended-kalman-filters, lidar, radar |
| Tier | [Beta (700 to 1,999 ★)](https://repo.masters-masters.com/en/ranks/box_office) |
| View on GitHub | [JunshengFu/tracking-with-Extended-Kalman-Filter](https://github.com/JunshengFu/tracking-with-Extended-Kalman-Filter) |

## Repository

Object (e.g Pedestrian, vehicles) tracking by Extended Kalman Filter (EKF), with fused data from both lidar and radar sensors.

The tier for repos with 700 to 1,999 ★. Published odds per card pulled: 6%. Rarity: Rare.

## More repos by JunshengFu

- [JunshengFu/vehicle-detection · ★ 674 · Python · Alpha](https://repo.masters-masters.com/en/repos/JunshengFu/vehicle-detection)
- [JunshengFu/driving-lane-departure-warning · ★ 241 · Python · Prototype](https://repo.masters-masters.com/en/repos/JunshengFu/driving-lane-departure-warning)
- [JunshengFu/Model-Predictive-Control · ★ 192 · C++ · Prototype](https://repo.masters-masters.com/en/repos/JunshengFu/Model-Predictive-Control)
- [JunshengFu/tracking-with-Unscented-Kalman-Filter · ★ 171 · C++ · Prototype](https://repo.masters-masters.com/en/repos/JunshengFu/tracking-with-Unscented-Kalman-Filter)
- [JunshengFu/semantic\_segmentation · ★ 115 · Python · Prototype](https://repo.masters-masters.com/en/repos/JunshengFu/semantic_segmentation)

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Data: GitHub · Illustration drawn by RepoMasters from the repo’s ID and its language color.