A bunch of state estimation algorithms

Implementation of Deep Statistical Solver for Distribution System State Estimation

fractional Kalman filter algorithms source code for SISO fractional order systems, including: fractional extended Kalman filter (FEKF), fractional central Kalman filter (FCDKF), fractional unscented Kalman filter (FUKF) and fractional particle filter (FPF)

Open source library for state estimation of a distribution network modeled in OpenDSS

Repository for the proposed DANSE method (accepted at EUSIPCO'23)

Code repository for the paper "State estimation in structural dynamics through RNN transfer learning".

Gamified application of the EKF with an eye to its business value

Implimentation of kalman filter for a vehicle with unknown location, noisy measurements using python

This repository contains code related to the pDANSE method (accepted at ICASSP'25)

Embedded micromouse robotics stack with localization, measurement optimization for rapid position estimation, and control on ESP32.

This code was developed as part of a broader team navigation project which also included path planning & exploration and HW deployment in robile platform . This submodule focussed on developing different methods (odom & velocity based) and tuning the Monte Carlo Localization (Particle Filter) stack within a ROS2 simulation environment.

Code for the concept paper presenting physics-aware neural networks for power quality state estimation

Here we will experiment with Extended Kalman Filter Localization packages in ROS

Open-source implementation of 12-State Kalman Filter and 15-State Extended Kalman Filter for asynchronous multi-rate sensor fusion, including Python and MATLAB implementations, synthetic dataset generation, and validation framework.

GNSS Tools For GTSAM

Created a Python program for the ConnectX game competition on Kaggle. Implemented strategies to place checkers strategically on a board to win or prevent opponent wins. Evaluated based on performance against other submissions in ongoing matches.