Questions tagged [kalman-filters]

The Kalman filter is a mathematical method using noisy measurements observed over time to produce values that tend to be closer to the true values of the measurements and their associated calculated values.

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Kalman filtering for position using GPS,accelerometer and speed sensors

I am working on tracking a vehicle under tunnel when GPS is lost. Whenever the vehicle in on the road, the GPS works fine and gives good accuracy but when the vehicle is under tunnel, the GPS is lost ...
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Estimating velocities from IMU Acceleration

I hope someone can help me to figure out the best way to solve my problem I'm trying to drive a Cuboid on V-rep simulator with velocities What I'm receiving is accelerations from an IMU (MPU9250 acc+...
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Kalman Filter | Why Shift the Belief Distribution

I am looking at the video lecture on Kalman Filter. I got some understanding that if the robot moves that we also shift the enviornment belief model accordingly (the same mean amount the robot moved). ...
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Tracking movement of audio speaker driver using images

I have a speaker emitting low-frequency sinusoidal wave and I have physically marked a curved edge on the speaker driver as shown in red in the image below, which I would like to track: I detect the ...
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Reduce Jitter in Live Kalman Filter

I have a stream of data over time that I have fed into a Kalman filter. This data represents the vertical displacement in time of a vehicle's rearwheel as it travels over a bump in the road. The ...
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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 ...
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Noise converges to wrong value in Unscented Kalman Filter with augmented state

I have implemented UKF with augmented state (concatenating state variable with noise variables) on a classical toy example. Object state consist of position and velocity in 2D space. My measurements ...
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Kalman Filter | Difference Between Minimizing the Mean Square Error (MMSE) & Maximizing Likelihood Value in Bayesian Estimation

I am going through data assimilation slides on Multi Sensor Data Fusion by Hugh Durrant Whyte and it mentions: The Kalman Filter, and indeed any mean-squared-error estimator, computes an estimate ...
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Separating Velocity and Position in a Kalman Filter

I have an implementation of Kalman filter for a tracking problem, with constant acceleration model. In this model: My State Matrix is: $$ X = [x, y , V_x, V_y, a_x, a_y];$$ My measurement Matrix is: ...
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Is it possible to detect or localize movement of objects using LPWA (or LPWAN) such as LoRa, DASH7, NB-FI?

Assume that there is a moving human in the room without any device (or receiver). Is it possible to detect or localize movement of objects using LPWA (or LPWAN) such as LoRa, DASH7, NB-FI by analyzing ...
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Fundamental questions about state-space and Kalman filters

I am a dsp guy, I only did a minimum of control theory back in university. While trying to grok state space analysis and (discrete time) regular Kalman filters, I am hitting a few questions that ...
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140 views

How to Reduce Phase Lag Caused by Kalman Filter

Background I have been developing a system using a moving robot with a distance sensor against another robot. I want to control these robots by estimating relative velocity and acceleration derived ...
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how to get the location long and lat out of the raw measurements?

I'am making a research about GNSS I used GNSS logger to collect measurements but couldn't understand how these measurements turn into location of long and lat? the picture below of the measurements ...
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Code implementation of Channel estimation based DFE Equalizer in matlab (or octave) without the the signal processing tool box

I want to implement a DFE in matlab without the signal processing toolbox: I have two filters ( FeedForward and FeedBack) with taps length equal to 15. I know the update equation of the LMS ...
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How to update Kalman Filter with n-th order state translation?

In Kalman Filter, the hidden state translation is defined by $X_t=F_tX_{t-1}+W_t$, where $X_t$ can be a vector or a single value. This is actually derived from Bayes filter, in which 1-th order markov ...
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142 views

why does DFE feedback filter matters?

I recently came across an article on the inventor of adaptative equalizer Robert Lucky, In this article : An Oral History by Robert Lucky (http://www.ieeeghn.org/wiki/index.php/Oral-History:...
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Can a Kalman Filter Be Applied Using Measurement-Space Dependent Sensors?

I'm currently attempting to apply a Kalman filter to track the angular position, velocity, and acceleration of a bike wheel, and I'm having a lot of trouble, so I want to check if I'm even applying ...
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How to set the measurement matrix of opencv kalman filter [OpenCV+Python]

I am working on a tracking application where I use the kalman filter to validate my current measurement of the position. I use the code from this question: How to find the probability of Kalman filter ...
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Rotation matrix covariance to quaternion covariance in attitude estimation

Given a $3 \times 3$ rotation matrix $\mathbf{R}$ with an associated $3 \times 3$ covariance matrix $\mathbf{P}$ how do I compute the associated $4 \times 4$ covariance matrix $\mathbf{Q}$ of the ...
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How to build intuition for tuning a Kalman Filter?

I'm working on designing a Kalman Filter for more accurately predicting the position of a ultrawideband RFID tag in an indoor space. Before testing with live data, I've been playing with randomly ...
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Kalman fitler to estimate position from velocity measurement

I am using the Kalman filter to estimate the position from velocity measurements. I implemented the filter, but the position estimate is not well enough (large RMSE and Covariance value). Some time ...
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Choosing Right Type of Filter for time series data

I am working on a temperature time-series data which is very noisy. I am trying to measure true low and ...
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Kalman Filter: Effect on covariance from frauded errorneous sensor

I have recently started to learn about Kalman filters and I am right now simulating a very simple model in Simulink giving a noisy sinewave (position) and its derivative (speed). I have implemented/...
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Kalman filter using only location information

I have never used a Kalman filter. Is it possible to implement a Kalman filter using only location information? In addition, if you can implement it, what kind of procedure should be used to program ...
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Kalman-Filter Estimate the position

I am quite new in this field and trying to learn Kalman-Filter but i am quite lost how to start my task. This is the file description Problem. I guess the state vector x must be the poistion of ...
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Kalman Filter System Model

I have multiple measurements to be fused and noise to be removed. As far as you know, can I use one reference measurement to be my system model? Thanks
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Kalman Filter for position : introducing acceleration estimates

I want to estimate the position on a 3D environment by introducing only acceleration estimates. Is that possible? If I use the extended Kalman Filter and introduce these estimates will I have the ...
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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 ...
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Structural time series model with multiplicative error term

I have a noisy time series measurement of a biological signal which I need to smoothen. I believe that the error of the measurement is proportional to the signal strength. I am currently working in R ...
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Filterpy Kalman Filter batch processing with multiple measurement sources

In pythons module for kalman-filtering, filterpy, there is a function batch_filter() to batch filter a list of measurements that then can be used for RTS-smoothing. ...
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121 views

Getting Vario (m/s) from a bmp180

I am building a variometer as a hobbie, this could be a duplicate from an existing question: How to use Kalman filter for altitude prediction based on barometer data? . Details follow: I have a ...
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Using an IMU for gravimetry and calculation of gravity anomalies

I am currently working on a project which seeks to utilize a tri-axial IMU to measure gravity anomalies caused by density variations in planetary crusts. The instrument will be attached to a Helikite ...
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Can anyone suggest algorithm for getting latitude, longitude co-ordinates from fusion of data from accelerometer, gyroscope and magnetometer?

Currently, I am trying to fuse the data from these sensors to get the new positions. I have an initial latitude, longitude position which I am using as the initial coordinates. Now by using the ...
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Fuse two sources of linear acceleration with a Kalman filter

How would I fuse two different sources of linear acceleration with a Kalman filter (perhaps linear acceleration readings from an IMU and from a dedicated accelerometer)? My state is defined by ...
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Kalman Filter EM Estimation of Covariances

The question might be very simple, but I get a strange result from Kalman Filter. Let us consider the simplest state-space model, the random walk plus noise: $$ y_{t} = x_{t} + \varepsilon_{t}\\ x_{t} ...
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Layman Description of the Kalman Filter

I want to know about Kalman Filter but i tried searching different links including Electrical Engineering StackExchange but the information available there was hardly digestible. All I am able to ...
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Converting an FIR Filter Model to a State Space Model for Kalman Filtering

I want to try and determine the true value of a quantity $\alpha[k]$ from observations of a related quantity $\vartheta[k]$ using a Kalman filter. The observations are of the following FIR filter form:...
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Why is the concept of a “state covariance matrix” necessary in estimation?

I'm currently taking a course in optimal estimation (and it's still very early in the course). Much of our work is based around the idea of a measurement model $y=Hx + v$ This model assumes our ...
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Coordinate frame in IMU/GPS Error-state kalman filtering

I just read this really nice paper "Quaternion kinematics for the error-state Kalman filter", according to this book "Principles-Multisensor-Integrated-Navigation-Applications" we have following ...
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203 views

Kalman Filter - How to combine data from sensors with different measurement rates?

I'm trying to implement a Kalman filter for tracking the position of a vehicle with the help of position data from GPS and Odometry measurements. The GPS data (WGS84 format collected from an app on an ...
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202 views

Kalman Filter Parameter Definition for Vehicle Position Estimation in Python

I'm relatively new to Kalman filter concepts and I would like to use it for estimating and tracking the accuracy of the position of a vehicle with GPS measurements (As a first step). However, I am not ...
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194 views

Error in using Kalman Filter for 2D Position Estimation in Python

This is my first question on DSP Stack exchange, so I apologise if it is poorly worded. I have some positioning data from a vehicle (GPX Format, collected through Strava) and want to use a Kalman ...
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Inconsistant Variation in BLE Beacon RSSI Values for Distance Measurement

I am developing an application to estimate the distance to a BLE Beacon using its RSSi values measured from a Mobile Phone. But when I started to collect data I could see that they varied so much that ...
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Position Kalman Filter fails to track a constant-acceleration path

I'm trying to build a discrete Kalman Filter that fuses accelerometer (acceleration) and GPS (position, velocity) measurements. However, I'm finding that my filter can't properly track a constant-...
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Using Kalman filter vs Extended Kalman filter for differential drive robot with IMU

I have an IMU that provides me with a heading that is pretty accurate and accurate encoders on the wheels of my differential drive robot which provides me with pretty accurate velocity but has ...
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Have you ever seen logarithmic burn-in on a Kalman filter before?

I'm reviewing a paper that uses a multiplicative factor $\ln i$ where $i$ is the number of steps since the Kalman filter was initialized. The idea is to slowly build confidence as the filter sees ...
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Kalman Filter Process Noise - Model Where It Vanished

I am trying to use the Kalman filter (the scalar version) to estimate the steady state of a set measurements which is a random process. I have used a constant dynamic model as the state equation, $$ ...
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Can Kalman filter remove 50 Hz noise?

I'm dealing with a brain stimulation. My EEG contains large spikes (>3 mV) when stimulation occurs. I want to remove the 50 Hz noise, but I can't use notch filter because it creates large artifacts. ...
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Model-based Kalman filtering a noisy signal

In a healthcare application, I need to calculate urine flow by differentiating the mass of urine emitted by a person over time. The measuring instrument consists of a load-cell under a fluid container,...
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How Do Particle Filters Get Velocity When Tracking with Pos Measurements

I am new to particle filtering. I can see when particle filters are used with Ensemble Kalman's, the velocity of the states are taken care of by the Kalman. When tracking using particle filters ...

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