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Questions tagged [unscented-kalman-filter]

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Does it make sense to have diverging Kalman gain and covariance when system accuracy worsens over time?

I've developed an UKF for a system, whose dynamics change slowly over time. The state & measurement equations are quadratic and linear equations fitted to experimental data in the following form: $...
square potato's user avatar
1 vote
0 answers
66 views

Which filter is suitable for reducing noise in feature detection?

I have a feature detection algorithm that is called FAST - Feature Accelerated Segmented Test. It's a very fast algorithm for finding feature points, e.g "corners" inside an image. Here is ...
euraad's user avatar
  • 405
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1 answer
210 views

Kalman filter in data fusion

I am very new to Kalman filter. I am doing a project using one sensor the track the sensor's position. I developed 2 methods to solve the position, one in better accuracy and one is less accurate. I ...
Ko Chunwai's user avatar
1 vote
0 answers
198 views

Derivation of the process noise covariance matrix for non linear system in UKF

I have a continuous (in time) non-linear system in the form $\dot{x}=f(x(t)) + Bu(t) + w(t)$ which I would like to track with a UKF. $w(t)$ represent white noise (in particular, the acceleration and ...
macia's user avatar
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3 votes
0 answers
598 views

Unscented Kalman Filter for Parameter Estimation (Tracking) of Amplitude Frequency and Phase of a Multi Component Harmonic Signal

I'm trying to implement an Unscented Kalman Filter that tracks the amplitude, frequency, and phase of a multi-component oscillatory signal. Below is an attempt using the ...
SuperCodeBrah's user avatar
0 votes
1 answer
99 views

Example for implementing the unscented kalman filter

Currently, I'm learning about the UKF and in order to understand it in a good way, I programmed it, however in order to see it working I need a problem to solve which I can't now find. Can you please ...
jon's user avatar
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1 vote
1 answer
252 views

EKF: IMU vs State Transition Model

Suppose you have an object you're interested in estimating the state of, ex position. Suppose you don't have a state transition model but you do have an IMU. Can the IMU be used to simulate a state ...
FourierFlux's user avatar
1 vote
1 answer
235 views

Kalman filtering with dynamic covariance/variance

What is the appropriate way to implement KF if your sensor confidence is time and observation dependent? Ex, you asses the quality of camera tracking by the percentage of features correctly matched by ...
FourierFlux's user avatar
3 votes
1 answer
513 views

How to determine covariance matrices $\mathbf P$, $\mathbf Q$, and $\mathbf R$ in Extended Kalman Filter

I am implementing an Extended Kalman-Filter and an Unscented Kalman-Filter for state and parameter estimation of a conveyer belt system. The problem is that I don't really know how to determine the ...
Tristan's user avatar
  • 31
-1 votes
1 answer
91 views

Are there any general heuristics for Kalman filter noise parameters

Are there any generally applicable heuristics for Kalman filter noise parameters? I am working with a non-linear unscented filter and getting an initial guess for the noise covariances $Q_k$ and $R_k$ ...
user2133814's user avatar
3 votes
1 answer
522 views

Kalman Filter - Deriving state transition function

I am relatively new to using Kalman Filtering. Currently I am trying to understand it and how to implement it in Matlab. I found a website with some nice examples that I would like to rewrite in ...
Matthias La's user avatar
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1 answer
91 views

How is a Particle Filter used to Estimate Parameters of a State Transition Function?

In the tutorials on particle filters that I have seen, it seems that the state transition function is already known. This example from Matlab, for example, states the the Plant or State Transition ...
Jim's user avatar
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0 answers
28 views

Parameter tracking using Augmented state vector approach and unscented Kalman filter

I'm trying to reproduce and extend figure 9 results in Nonlinear dynamical system identification from uncertain and indirect measurements"HU Voss, J Timmer, J Kurths - International Journal of ...
ccc's user avatar
  • 111
1 vote
0 answers
161 views

Kalman Filter: Difference between sensor input and control input

I recently saw a matlab sensor fusion example which combined IMU and GPS data for drone localization. What was surprising about it was that the IMU was used to predict future behavior of the system as ...
FourierFlux's user avatar
1 vote
1 answer
152 views

What is the name for a constant-heading Kalman filter model for vehicle tracking?

When applying Kalman filtering to estimate the position of a car, there are several different vehicle dynamics models that you could use. One of the simplest is "constant velocity" or CV, ...
Kerrick Staley's user avatar
4 votes
1 answer
309 views

Application of UKF on quaternions

I'm trying to perform a state estimation on quaternions to predict the future orientation of a human head. The only sensor data I can obtain (from the AR headset) is the current orientation of the ...
chronosynclastic's user avatar
0 votes
2 answers
992 views

Refining accelerometer noise using Kalman filter

I have read that one of the uses of the Kaman filter is to refine the noisy sensor measurements. I am using an accelerometer to get the position by integration and want to use Kaman filter to refine ...
M.Saeed's user avatar
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5 votes
1 answer
1k views

How to Realize the Sigma Point Sampling Function in Unscented Kalman Filter?

Recently I'm learning the unscented kalman filter (UKF). When designing the unscented kalman filter, it involves a non-linear function to generate the sigma points and then use the system non-linear ...
wenkang's user avatar
  • 53
2 votes
2 answers
1k views

Is there a difference what measurement units use in covariance matrix

The R matrix in the Kalman filter contains measurement noise. Diagonal elements of the matrix is the power of standard deviation. Is there a difference what measurement unit to use for standard error ...
Gluttton's user avatar
  • 388
6 votes
3 answers
1k views

Unscented Kalman Filter - Multiple Consecutive Measurement Updates

In trying to implement an Unscented Kalman Filter (UKF), I have come across the issue of what to do when my measurement signals come in at a different rate than my control inputs, which I use in the ...
theo1010's user avatar
0 votes
1 answer
719 views

Can state covariance matrix in Unscented Kalman filter contain negative values?

On the one hand covariance matrix can't contain negative values by definition, but as far as state covariance matrix innovated by subtraction: $$\mathbf{P} = \bar{\mathbf P} - \mathbf K\mathbf P_{z}\...
Gluttton's user avatar
  • 388
1 vote
0 answers
248 views

Unscented Kalman Filter - estimation of two parameters

I am working with Unscented Kalman Filter (UKF) in thermal modelling of a box. I have 3 state variables ($T$ temperature, heating $h_h$ and cooling rates $h_c$) in my model and I am observing just ...
mikel's user avatar
  • 43
2 votes
1 answer
174 views

Implementing Kalman filter or extended or unscented with only position information

I am new to Kalman filter. Is it possible to use a Kalman filter with just the position information of the target? I am so confused with states and measurement.
Manish Sharma's user avatar
4 votes
1 answer
729 views

Is acceleration noise modelled differently in EKF and UKF Kalman Filters?

In a lecture on basic Kalman filter, I came across the following assumption about acceleration noise. Every component of the noise vector $\nu$ is itself a product of time and acceleration values. ...
farhanhubble's user avatar
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0 answers
50 views

Which equation should I use to compute the Extended Kalman Filter?

Compute the Extended kalman filter can be done in several ways. The first one compute the convariance matrix $P(t)$ from the Riccati Equation: $$\dot{P} = F(t)P(t) + P(t)F^T(t) - P(t)H^T(t) R^{-1}H(...
euraad's user avatar
  • 405
2 votes
0 answers
163 views

Check if I has right: Is this the Extended Kalman Filter

I have learn the Kalman-Buncy filter for the LQG controllers. I know that this is a signal processing forum and not robotics not math forum. But Extended Kalman Filters are daily discussed here. ...
euraad's user avatar
  • 405
5 votes
2 answers
918 views

Explain the Adaptive Part of Adaptive Algorithms - Kalman Filter and Least Mean Square / Constant Modulus

General questions: Is the Kalman filter (they have used Unscented Kalman Filter) adaptive or not? Is the Unscented Kalman Filter used in the paper an adaptive algorithm? Adaptive algorithms such as ...
Ria George's user avatar
4 votes
1 answer
251 views

Likelihood of Unscented Kalman filter

Short version: How to calculate a likelihood of Unscented Kalman filter? Long version: Likelihood for linear Kalman filter (KF) is: $$\mathcal{L} = \frac{1}{\sqrt{2\pi S}}\exp \left[-\frac{1}{2}\...
Gluttton's user avatar
  • 388
0 votes
1 answer
116 views

Unable to understand how the paper simplifies the covariance matrix - Kalman filter

The paper Convergence Analysis of the Unscented Kalman Filter for Filtering Noisy Chaotic Signals presents the convergence analysis of Unscented Kalman Filter download http://www.eie.polyu.edu.hk/~...
SKM's user avatar
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0 votes
1 answer
317 views

Conceptual Question on equalization technique in rayleigh fading channel based on a paper

Question Link http://www.raymaps.com/index.php/theoretical-ber-of-m-qam-in-rayleigh-fading/ gives theoretical expressions for BER in Rayleigh fading channel. Can I use the expression for 64-QAM in ...
SKM's user avatar
  • 621
0 votes
0 answers
223 views

Making Unscented Kalman Filter Robust for Nonlinear Parameter Estimation Problems

So I have built code for an Unscented Kalman filter that can take any specified state and measurement dynamics. I have tested it on various linear problems and it works well, as expected. The main ...
spektr's user avatar
  • 263