Questions tagged [kalman-filters]

The tag has no usage guidance.

Filter by
Sorted by
Tagged with
2
votes
0answers
33 views

Relationship between the infinity norm of estimation error and the trace of estimation error covariance matrix in Kalman filter

I am working on designing an interconnected distributed control system. In this system, I need to use Kalman filter because the measurements are noisy. I have two questions: 1 - What is the ...
1
vote
0answers
28 views

What is the original paper using Extended Kalman Filter for joint state and parameter estimation [closed]

The title says it all. I would like to know which was the first paper to apply the Extended Kalman Filter to jointly estimate the state plus some parameter of the system. (by extending the system ...
3
votes
0answers
58 views

Relationship and interpretation of "discrete" and "continuous" covariance matrices in Kalman Filtering

I am quite confused about the interpretations/implementation of the system and measurement noise covariance matrices for the continuous and discrete time Kalman Filter. What I want is to initialize ...
0
votes
1answer
58 views

Why not to calibrate accelerometer in IMU filters?

I have been reading various research papers regarding IMU filters and I came to the question of why do we not need to calibrate the accelerometer values as we do for the gyroscope and magnetometer?
0
votes
1answer
36 views

Complementary filter in MPU_6050 is giving me the wrong answer when the system is accelerating

So I am using a complementary filter to find the attitude in my quadcopter, doing the following $$\text{angle} = 0.98\cdot (\text{angle}+\text{dt}\cdot \text{angle_rate})+0.02\cdot \text{...
1
vote
0answers
19 views

how do i formulate a kalman filter for an upwash coefficient?

I want to make a kalman filter that will estimate the upwash coefficient $C_{\alpha_{up}}$ my state vector: $ X_k=[u \ v \ w \ C_{\alpha_{up}} ]^T $ My measurement vector: $ Z_k =[\alpha_m \ \beta_m ...
2
votes
1answer
106 views

Kalman filter for sensor fusion — what is the advantage?

Is there any meaning of using Kalman Filter for cases when you do not have good statistical model of the system? For example, if you have a drone and it has IMU sensor and GPS sensor. You do not have ...
1
vote
1answer
89 views

Extended Kalman Filter formulation

For a nonlinear system, $$ \begin{align} &{\boldsymbol x}(k+1)={\boldsymbol f}({\boldsymbol x}(k),{\boldsymbol u}(k),{\boldsymbol w}(k)) \\ &{\boldsymbol y}(k)={\boldsymbol h}({\boldsymbol x}(...
3
votes
2answers
4k views

Kalman filters vs. state observers

What is the difference between a state observer and a Kalman filter? Having implemented various types of Kalman filters, I'm still a bit confused, mainly because state observers require the selection ...
2
votes
1answer
176 views

Can a load be estimated using a Kalman filter?

I have a system with a motor, some masses, damping and springs. One of the masses is loaded with an unknown external force F. I want to estimate the force F using data of the motor (mainly current). ...
11
votes
1answer
2k views

Observability using the Discrete Extended Kalman Filter (EKF)

I have built (several) discrete Extended Kalman Filters (EKF). The system model I am building has 9 states, and 10 observations. I see that most of the states converge except one. All except 1-2 of ...
9
votes
2answers
754 views

Types of state observers/estimators actively used in the industry?

Most introductory books on control theory usually start their state observation part by introducing the Luenberger observer, and after that they might continue by introducing the Kalman filter. When ...