Skip to main content

Questions tagged [estimation]

In signal processing, estimation is a technique for approximating an unobserved signal from an observed signal containing noise.

Filter by
Sorted by
Tagged with
0 votes
1 answer
26 views

In EKF should Kalman Gain converge to a specific value?

I have implemented an EKF using the standard predict and update equations in order to perform state estimation of a vehicle with multiple sensors. The model has process covariance matrix $Q$ and each ...
useeeeer132's user avatar
0 votes
1 answer
33 views

Downconversion and CFO estimation after package detection

I'm currently working on generating a function to simulate a passband transmission. In my simulation, I assume that the received signal is twice of my transmitted signal (without adding any noise and ...
Webcy's user avatar
  • 1
0 votes
0 answers
78 views

Signal Separation (constant modulus)

I am trying to separate two source signals, that have constant envelope. The things is that the mixture if forming a Torus, and I am not sure about which algorithm is the most adapted to the situation....
cassidi's user avatar
0 votes
0 answers
19 views

Estimating IMU biases without using any external aid

Assuming that Inertial Measurement Unit (IMU) contains accelerometer and gyroscope, I want to estimate the bias in each of the sensors. We know that accelerometer and gyroscope have biases which ...
user146290's user avatar
0 votes
0 answers
19 views

Kalman filters which only update a subset of variables?

What is the general approach to updating a subset of variables with a kalman filter? IE sensor X only updates variable Y. What I'm a little bit confused on is how the covariance would be propagated.
FourierFlux's user avatar
0 votes
0 answers
22 views

Two meanings for "innovation" in Wiener filter are the same?

This is related question to A question about Wiener filter based on Linear Estimation by Kailath, based on the textbook Linear Estimation by Kailath. In that link I talk about how I first learned what ...
monad's user avatar
  • 1
0 votes
0 answers
21 views

A question about Wiener filter based on Linear Estimation by Kailath

In my linear estimation class based on the textbook Linear Estimation by Kailath, we went through the process of finding LLSE of $\hat{x}(t+\lambda)$ for fixed $\lambda$ given $\{y(\tau)|-\infty<\...
monad's user avatar
  • 1
2 votes
1 answer
100 views

Why use MUSIC/ESPIRIT algorithms to estimate DOA when we can use beamforming?

I am trying to understand why we need MUSIC/ESPRIT algorithms to estimate the direction of arrivals. Why can we not use phased arrays to get the exact DOA (and not an estimate of the DOA) via beam ...
RajaKrishnappa's user avatar
0 votes
1 answer
51 views

Looking for an online course

I work for a company with expertise in electromagnetics physics, specifically dealing with time domain-based simulation software. We routinely need to transform our results into frequency domain, ...
DrEarlGray's user avatar
0 votes
0 answers
13 views

Advantages of Euler vs Quaternion vs Axis-Angle Paramertization

I have spent a bit of time studying attitude estimation and I noticed that uncertainty of orientation can basically be represented in three forms. Euler angles, Axis Angle and Quaternions. Quaternions ...
FourierFlux's user avatar
0 votes
0 answers
23 views

Fusing multiple IMUs in EKF framework

What is the approach to fuse multiple IMUs in EKF framework? Normally you take the IMU as the motion model and the sense step to consist of other sensors but when have multiple IMUs operating, what is ...
FourierFlux's user avatar
0 votes
1 answer
49 views

How to estimate temperature based on resistance thermal dependency?

My question is tightly related to my different question. Let's say I have an inverter fed three phase induction motor drive where in the braking phase (when the motor operates in a generator mode) the ...
Steve's user avatar
  • 397
1 vote
0 answers
30 views

Temperature estimation via Kalman filter

Based on the recommendation I would like to ask you for your opinion regarding my question I have asked on different forum.
Steve's user avatar
  • 397
0 votes
0 answers
36 views

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
0 votes
1 answer
41 views

IMU gravity tracking

I'm interested in tracking the gravity vector for a UAV supposing we don't have external input or GPS. I think a solution to the problem is as a follows: We have a past gravity direction vector which ...
FourierFlux's user avatar
0 votes
0 answers
21 views

MatLab - System Identification Toolbox vs Code - discrepancies and small fit percentages

I need help understanding what in what is wrong with what I am doing, or why is this happening. So basically I have two tables and one variable: ...
justaguy's user avatar
2 votes
0 answers
83 views

What happens when Kalman filter is applied on a memoryless system?

I'm trying to set up a Kalman filter for my system $$ x_{k+1} = f(u_k) $$ $$ z_{k+1} = g(x_{k+1}) $$ and found that while the filter "works" (able to reduce rmse from 1.5% in the open loop ...
square potato's user avatar
1 vote
0 answers
24 views

How to tune the coefficients of Polynomial Models in MatLab System Identification toolbox

I have such setting: Where $Y_M(S)$ is the transfer function of the model I am trying to approximate with $Y_U(S)$, what I have is the data of the signal corrupted with noise. I am trying to create a ...
justaguy's user avatar
4 votes
1 answer
210 views

FFT-based phase estimation better than CRLB in MATLAB simulation

I am trying to understand the concept of CRLB for a simple sinusoid in AWGN with a simulation in MATLAB. According to Kay (p. 57) the CRLB for phase estimation is: $var\{\phi\}=\frac{2(2N-1)}{SNR\cdot ...
HaLoe's user avatar
  • 43
0 votes
0 answers
15 views

Finding oscillation frequency in a harmonic polluted signal [duplicate]

I would like to find periodicity and the oscillation frequency in a signal. I used this simple MATLAB code which works find for some signals, but for a harmonic polluted signal like the one given ...
user70703's user avatar
0 votes
0 answers
31 views

Value of EKF when fusing two estimates of the same state

I'm looking at fusing the output of two SLAM packages. In the examples code given an EKF is referenced for this fusion but I can't find the implementation. I don't understand the value of the EKF ...
FourierFlux's user avatar
4 votes
2 answers
145 views

Estimating spectrum with regularly missing samples from data

Suppose: $$ s(t) = \sin(2\pi{f_0}t) $$ Suppose I'm sampling the signal with a sample frequency $f_s >2f_0$ . However, every $M$ samples there is a dead-time of $L$ samples. Traditionally, the (...
Sammy Apsel's user avatar
1 vote
1 answer
140 views

Calculation of the LMMSE Channel Estimator

Consider a MIMO system equipped with $N_t$ transmit antennas and $N_r$ receive antennas. The received signal over $L$ snapshots are given by $$Y = H X + Z,$$ where $X$ is the $N_t \times L$ transmited ...
maphado fan's user avatar
1 vote
0 answers
169 views

How to implement maximum likelihood (ML) detector in MATLAB?

Consider the MIMO system which has $N_t$ antennas at transmitter and $N_r$ antennas at receiver and uses Generalized space shift keying (GSSK) modulation. The received signal is given by: $$Y = H X + ...
Heretolearn's user avatar
1 vote
3 answers
229 views

How can I estimate the 2 parameters of this signal?

I have a digital signal of fixed length (e.g. 100 samples). Somewhere within this signal is a contiguous region characterized by "low variance". The remainder of the signal is characterized ...
Harry's user avatar
  • 183
1 vote
0 answers
43 views

Proof that the estimation error in the LMS filter is uncorrelated

I need to demonstrate that the estimation error in the LMS adaptive filter is white. The LMS equations are the following: $y(n)={\mathbf{\hat{w}}}(n)^H\mathbf{u}(n)$ $e(n)=d(n)-y(n)$ ${\mathbf{\hat{w}}...
Andrea Tani's user avatar
8 votes
1 answer
839 views

What is the adjoint of a linear operator and why is it useful?

The concept of linear operators and their adjoints arises frequently in some corners of signal processing, but is not particularly well documented, at least from a signal processing perspective (you ...
Gillespie's user avatar
  • 1,906
4 votes
2 answers
309 views

Smallest Eigenvalue in the Derivation of the MUSIC Algorithm

I am seeking clarification on a particular step in the derivation of the MUSIC algorithm as presented in a specific paper. Here, there is an intermediate step I cannot follow and I would appreciate ...
Naetmul's user avatar
  • 145
0 votes
0 answers
92 views

Variance of phase estimation using FFT as a function of SNR, frequency and signal length

I have looked at previous questions on this topic but I am still unsatisfied. I want to predict how accurately I can estimate the phase of a tone as a function of signal SNR, tone frequency, and the ...
LDPC's user avatar
  • 195
2 votes
2 answers
146 views

Implementation of biased estimators

In Fundamentals Of Statistical Signal Processing: Estimation Theory page 19, Kay mentions a biased mean square error estimator for $\mu$ where the samples $x\sim\text{N}(\mu, \sigma^2)$. The suggested ...
Gideon Genadi Kogan's user avatar
2 votes
0 answers
75 views

Optimum Measurement of Sine Wave Amplitude in Noise

There are many related questions posted about estimating sine wave parameters, and this one is closest: Measuring amplitude of a pure sine wave of known frequency close to the noise floor, but none ...
Dan Boschen's user avatar
  • 52.3k
4 votes
1 answer
147 views

Understanding Maximum likelihood detector expression?

Consider the MIMO system which has $N_t$ antennas at transmitter and $N_r$ antennas at receiver and uses Generalized space shift keying (GSSK) modulation. The received signal is given by: $$Y = H X + ...
Heretolearn's user avatar
7 votes
1 answer
211 views

Noise leakage problem with least square estimation in the frequency-distance domain

I have data $d$ recorded from an antenna of sensors. These data are composed of a Gaussian noise $n$ and a signal $s$ which I try to estimate. This signal propagates on the antenna with frequency ...
User327201's user avatar
0 votes
0 answers
46 views

Modelling problem

Considering a finite-length impulse response $h[n]$ of length $M $ (which amounts to considering $h[n] = 0,$ for $n \geq M$). The data model, with additive disturbance, is then written as: $$y[n] = ...
Jacob's user avatar
  • 1
1 vote
2 answers
126 views

How to generate ground truth in constant velocity Kalman simulation?

I'm trying to simulate a particle going from (-3,0) to (3,0) with a constant velocity and some noise (e.g. the particle is a quadcopter trying to fly at constant velocity, but may be pushed by gusts ...
IMK's user avatar
  • 11
1 vote
0 answers
45 views

Variance of Value Expressed as Number of Changing Bits

I consider values physical measurements, expressed as variables of type int16, uint32, float ...
Yair M's user avatar
  • 305
2 votes
2 answers
152 views

Clipping detection algorithm for a sinusoidal signal with noise and unknown amplitude in an online fashion

My problem is the following: I am sampling data from a sine signal Samples come in a online fashion (more and more data incoming through time). The device does not have a lot of memory so it is ...
A.Eng's user avatar
  • 21
4 votes
1 answer
72 views

How to Estimate a Multi Channels and Multi Kernels Convolution Kernel (Deep Learning Style) Given the Input and Output Images

Is it possible that can estimate convolutional kernel that have multi channels and multi filters ? I saw answer from this to link to estimate kernel for one channel and one filter (Estimating ...
Mint Int's user avatar
3 votes
1 answer
181 views

Estimating the Most Likely Harmonic Signal in a Spectrogram

Experimental data description: below image is from spectrogram of doppler radar return as I walk toward sensor. Bright sinusoid shape modulated with frequency F is from motion of small retroreflector ...
John Beale's user avatar
0 votes
0 answers
99 views

Noise variance estimation

could anyone recommend some articles how to estimate noise variance for the single carriers system with burst mode transmission (preamble+data TDMA)? My goal at the beginning is to develop skills how ...
dcs's user avatar
  • 45
1 vote
0 answers
126 views

Mean squared error between white noise and colored noise

While studying the whitening filter, I still can't come up with an intuitive and reasonable explanation of why a whitening filter is needed. As this question and its answer mentioned, I understand ...
Emm386's user avatar
  • 155
2 votes
0 answers
67 views

Estimation of time-varying velocity

Objective: Estimate the mechanical tension of a cable using the velocity of the waves travelling along it. Experimental setup: I have a cable in tension equipped with accelerometers. I measure a ...
User327201's user avatar
1 vote
1 answer
71 views

What are the Kalman filter capabilities for the state estimation in presence of the uncertainties in the system input?

I have a question regarding the capabilities of the discrete Kalman filter for estimation of the unmeasurable state variables of a dynamic system. In the time being I have been using a discrete ...
Steve's user avatar
  • 397
1 vote
0 answers
191 views

Sensor Fusion of Two Same Type of Data

I have an object moving with sinusoidal motion. I estimate the position of the object using lidar and camera separately. Then I want to fuse these two estimation data in the optimal way. For example I ...
guidolard's user avatar
1 vote
1 answer
77 views

What's the best way of modeling 3d target motion with only 2d angle observations?

A maneuvering target is flying in 3d cartesian space, but a sensor (passive infrared or mic array, etc.) can only observe it in polar coordinate with 2d orientations (azimuth, elevation). For ...
Steven Ding's user avatar
2 votes
1 answer
1k views

Why does sequential update of Kalman Filter work when you have multiple sensors?

If you are using a kalman filter with multiple sensing sensors there are two ways to fuse them. One way is doing a single observation step where you include all the sensors in a single vector and a ...
FourierFlux's user avatar
0 votes
2 answers
217 views

Why do I need to multiply the frequencies with a number, to get correct "shift" in the bode plot?

Assume that we got a sine wave function $$u(t) = A\sin(2\pi \omega(t)t)$$ Where the frequency $\omega(t)$ changes over time $t$ and $A$ is the amplitude. Assume that we apply that $u(t)$ signal onto a ...
euraad's user avatar
  • 405
1 vote
1 answer
166 views

IMU state estimation Covariance updating

EKF filter normally has a predict + update step, I am curious - how do you evolve the covariance of the state without one of the steps? In essence I want to evolve the state of an object using an IMU ...
FourierFlux's user avatar
0 votes
0 answers
175 views

Why MUSIC algorithm fail when the antenna spacing is larger than half wavelength?

I'm studying MUSIC algorithm for far-field DOA estimation. I found that when the antenna spacing $d$ is larger than half wavelength $(\frac{\lambda}{2})$, the algorithm fails and the spatial spectrum ...
McZhang's user avatar
  • 73
1 vote
0 answers
209 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
  • 53

1
2 3 4 5
9