In a dynamic model x(k+1) = a*x(k) + w z(k+1) = h*x(k+1) + v In real application, how to get the noise variance matrix R of v?...

In a dynamic model x(k+1) = a*x(k) + w z(k+1) = h*x(k+1) + v In real application, how to get the noise variance matrix R of v? Generally is it a time-variant value which should be estimated from the random signal z(k) itself? Or is it predetermined by the sensor property? Thanks.

hi ppl, i would like to know how do we implement a kalman filter in smoothing data from a noisy sensor.. its urgent pz help

hi ppl, i would like to know how do we implement a kalman filter in smoothing data from a noisy sensor.. its urgent pz help

hi ppl, i would like to know how do we implement a kalman filter in smoothing data from a noisy sensor.. its urgent pz help

hi ppl, i would like to know how do we implement a kalman filter in smoothing data from a noisy sensor.. its urgent pz help

When you have a digital sensor (say a quad detector for example), how do we estimate the SNR if we are using say a Kalman filter? My own guess is...

When you have a digital sensor (say a quad detector for example), how do we estimate the SNR if we are using say a Kalman filter? My own guess is that it will be more or less deterministic baring quantisation noise.

Hi all. I'm working with submerged vehicles; ROVs and AUVs. I need to learn about control and navigation systems for these things, and would...

Hi all. I'm working with submerged vehicles; ROVs and AUVs. I need to learn about control and navigation systems for these things, and would like pointers to literature. Anything, from "N&C for dummies" to the latest IEEE Journal articles, is of interest. I appreciate any help. Rune

Hi, Im a fourth year student and am currently working on a project where I am attempting to track the position of a racecar in the form of a...

Hi, Im a fourth year student and am currently working on a project where I am attempting to track the position of a racecar in the form of a strapdown INS. I am trying to use a 2-axis accelerometer(x,y), z-axis gyroscope and also have GPS coordinates available. I have been directed to look into Kalman filtering however after much reading I am still unsure about how to actually apply this to the d...

Hi, i'm searching for solutions to the exercises in the book from Brown and Hwang. Because i work through the book in a autodidactic manner,...

Hi, i'm searching for solutions to the exercises in the book from Brown and Hwang. Because i work through the book in a autodidactic manner, the solutions would be a nice support. (i don't need/have already the accompanying diskette) Very much thanks for any (even rudimentary) help :) Johann Blaser

Can anyone direct me to resources on any of the following topics, encountered during research on IIR filtering... alternatively, a...

Can anyone direct me to resources on any of the following topics, encountered during research on IIR filtering... alternatively, a brief explantion would be appreciated... 1. relatively prime polynomials 2. Pade approximation 3. McMillan degree 4. Hankel singular values 5. Schur complement 6. Kalman filters 7. persistently exciting 8. Sylvester Matrix Now there's a mouthful!

Hi everybody, I have to do a research mini project on the following techniques. 1- Kalman 2- Complementary Even just some tips/links on...

Hi everybody, I have to do a research mini project on the following techniques. 1- Kalman 2- Complementary Even just some tips/links on where to start and maybe how I might be able to add a practical element to my project (e.g a basic matlab script). Considering my knowledge of DSP is somewhat limited, what fundamental DSP aspects do I need to know before I can delve into these 2 techn...

When would you use one versus ther other eg suppose you need to it detect when a robot is falling over. I assume the rate gyro gives velocity...

When would you use one versus ther other eg suppose you need to it detect when a robot is falling over. I assume the rate gyro gives velocity which can be integrated to get position. Accelerometer has to be integrated twice to get position - I expect you could use a Kalman filter or some such. I am just confused when one versus the other is used.I saw an article somewhere which says you need ...

Hello, I am trying to integrate GPS and IMU using kalman filter. As the first step in the path i am trying to simulate the GPS/IMU using...

Hello, I am trying to integrate GPS and IMU using kalman filter. As the first step in the path i am trying to simulate the GPS/IMU using matlab.If anyone as worked in this field please give me suggestion or reference. waiting for reply praveen

Hi All, Can I know from an experienced and/or knowledgable guy out there--- 1). What is the good choice of "Short-time-stationary" window length...

Hi All, Can I know from an experienced and/or knowledgable guy out there--- 1). What is the good choice of "Short-time-stationary" window length in the ECG case? 2). What is the sufficient no. of AR parameters to model ECG well enough for filtering? 3). Besides instrumentation noise which other artefacts can be modeled as "white". Anticipating enlightening responses, ...

OK. This is sort of off the wall, and I know that the best practical answer is probably "approximate it with a lumped-paremeter system and use...

OK. This is sort of off the wall, and I know that the best practical answer is probably "approximate it with a lumped-paremeter system and use a Kalman filter". But: Assume that you have a signal that has an irrational spectra (lots of 1/f effects, specifically). Is there a way to estimate the signal content _directly_, without approximating it as a signal with a rational spectrum ...

I am struggling with a problem in which the states and measurements are both implicit in a constraint of the form (mx-bx)^2/(1+sx)^2 +...

I am struggling with a problem in which the states and measurements are both implicit in a constraint of the form (mx-bx)^2/(1+sx)^2 + (my-by)^2/(1+sy)^2 = 1 where mx, bx are measurements and bx, by sx, sy are states to be estimated. The states are generally constant but occassionally exhibit discontinuities, and it is these discontinuities which I would like to track. I have been tre...

I'm beginning a University research project that will be doing some pretty intense signal processing (a software defined radio, including a...

I'm beginning a University research project that will be doing some pretty intense signal processing (a software defined radio, including a 17-state Extended Kalman Filter) on an FPGA. I would like to ask anybody with experience in this area to comment on whether VHDL or Verilog would be an appropriate choice for this DSP design. Is there much difference in the logic synthesis or ease of prog...

A little while back I posted a question asking if anybody knew who invented RLS. Most people said Kalman. I recently found out in a paper that it...

A little while back I posted a question asking if anybody knew who invented RLS. Most people said Kalman. I recently found out in a paper that it was Guass!! Although this lay unused or undiscovered until 1950 by a guy called Plackett who re-discovered Guasses work. R.L.Plackett 1950 "Some theorems in least-squares", Biometrica,37,149-157

Hi, I have a disagreement with friend over if an observable that depend on lagged observable, should be called a state variable. I have the...

Hi, I have a disagreement with friend over if an observable that depend on lagged observable, should be called a state variable. I have the following system: xt=u+z(1,t-1)+x(t-1)+d·[y(t-1)-x(t-1)]+e(x,t) yt=u+z(2,t-1)+y(t-1)-d·[y(t-1)-x(t-1)]+e(y,t) z1 and z2 are AR(1) processes z(1,t)=p1z(1,t-1)+e(1,t) z(2,t)=p2z(2,t-1)+e(2,t) The observations are xt and yt I say the state varia...

Hi, I'm looking for someone familiar with the Singer acceleration model. Could such a person explain to me why Singer makes no assumption...

Hi, I'm looking for someone familiar with the Singer acceleration model. Could such a person explain to me why Singer makes no assumption on the sampling rate and the nyquist theorem? How can he say things such as the correlation coefficient goes to infinity, when it is actually bounded by 1/2T where T is the sampling period? This is driving me bananas!! thnaks This message was se...

Hi at all I'm currently designing a fullstate feedback controller with the following state space A = [ 0.9999066, -0.0069878;-0.0008812 ...

Hi at all I'm currently designing a fullstate feedback controller with the following state space A = [ 0.9999066, -0.0069878;-0.0008812 0.9178842]; B = [-0.0337198 0.0118804]'; C = [-1.0340817 -0.0915291]; D = [0]; and the feedback gains K = [-2.0831 0.9667]. The controller itself together with the kalman filter to estimate the states works without any problems. However, to use a ...

Does any one know good material on tracking single sound source using only two microphones on a dummy head.I have seen kalman filter tracking...

Does any one know good material on tracking single sound source using only two microphones on a dummy head.I have seen kalman filter tracking for constant velocity targets etc in case of radar applications but i dont know how to use these in case of sound sources. Thanks