Sources of noise in geostationary satellite attitude determination simulation

In summary, the conversation discusses the use of extended kalman filtering for satellite attitude determination using sun Earth sensors and gyro modelling. The sources of error in determination of satellite attitude are also mentioned, including alignment error, non-orthogonality error, bias, scale factor error, and random walk error. The conversation ends with a request for information on sources of noise-free measurements in a satellite.
  • #1
shakeel001
7
0
I am doing satellite attitude determination simulation using sun Earth sensors and Gyro modelling .I am using extended kalman filtering for attitude determination.

the sequence of operations I am doing are
% Simulation data
% Spacecraft data
% Gyro data
% Sensor data.
% Control system initialization
% Generate the orbit
% el = [a,i,W,w,e,M]. The spacecraft is in geostationary orbit
% Initial conditions at equinox
% Sun and Earth vectors
% Run the simulation

I need to know the sources of error in determination of satellite attitude.How can I compare that the estimated value is correct.why the gyro is noisy always and what are the sources of errors which shall results to get noisy readings of sensors or other actuators.
I shall be very grateful to all for help in this regards

Thanks again in advance for your time and efforts
 
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  • #2
There are several error sources. Some are
  • Alignment error: The gyro axes are not pointing where you think they are. The IMU case might be misaligned, and the gyros might be misaligned inside the case.
  • Non-orthogonality error: The gyros axes are not truly orthogonal to one another.
  • Bias: A non-rotating object will get a non-zero reading. Making matters worse, the bias tends to drift over time.
  • Scale factor error: The multiplicative factor used to convert counts to engineering units is not quite right. Like bias, scale factor error isn't quite constant. It can vary with temperature, how old the gyro is, and other factors.
  • Random walk error: Even if everything else goes right, a gyro still has the basic problem of measuring a noisy signal. Assuming this is white, the output of a gyro is integrated white noise: a random walk.

Gyro spec sheets specify limits to many of the above; almost all have a random walk spec, sometimes called Allan Variance.
 
  • #3
an you quote one example of each

1. Scale factor error which is temperature dependent

2. Random walk error

what are the sources of getting noise free measurements having sun,star and gyro or any other sensor which can provide noise free measurements in a satellite.

Thanks you very much and Regards
 
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  • #4
There is no such thing as a noise-free measurement. Every sensor has errors. Part of your job is to properly characterize these errors. As for the source of the measurement, that's your job too. Your simulation needs to provide the truth data to the sensor model.

Writing a simulation engine has been the subject of many aerospace engineers masters theses. Using some pre-built simulation engine is typically an upper level undergraduate / lower level graduate aerospace engineering class. Spacecraft sensors, and modeling them, is often yet another class (or multiple classes; that topic is open-ended).

In other words, you are asking for (demanding in a big font!) a synopsis of multiple advanced classes. You might want to rethink your position here.
 
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  • #5



I can provide some insight into the sources of noise in geostationary satellite attitude determination simulation. One of the main sources of noise in this type of simulation is measurement errors in the sensors. Sun Earth sensors and Gyro modelling can have inherent errors that can affect the accuracy of the attitude determination. Additionally, external factors such as solar radiation and magnetic fields can also introduce noise into the sensor readings.

Another source of noise could be errors in the simulation data or spacecraft data. If the initial conditions or orbit parameters are not accurately represented in the simulation, it can lead to discrepancies in the attitude determination.

To compare the estimated values with the correct values, it is important to have a reliable and accurate reference system. This can be achieved through ground-based measurements or by using a known and stable satellite as a reference.

The gyro is often noisy due to mechanical imperfections and external disturbances. It is important to properly calibrate the gyro and account for any external disturbances in the simulation to minimize the noise.

Sources of errors that can result in noisy readings from sensors or other actuators include temperature variations, electromagnetic interference, and mechanical vibrations. It is important to consider all of these factors when designing and conducting the simulation.

In conclusion, to ensure accurate and reliable results in geostationary satellite attitude determination simulation, it is crucial to carefully consider and account for all potential sources of noise and errors. This can be achieved through proper calibration, accurate simulation data, and accounting for external disturbances.
 

Related to Sources of noise in geostationary satellite attitude determination simulation

1. What is the definition of "noise" in the context of geostationary satellite attitude determination simulation?

Noise in this context refers to any random or unwanted signals or disturbances that can affect the accuracy of the simulation. This can include external factors such as environmental conditions or internal factors such as instrument errors.

2. What are the main sources of noise in geostationary satellite attitude determination simulation?

The main sources of noise in this type of simulation include atmospheric turbulence, thermal variations, electromagnetic interference, and sensor measurement errors.

3. How do these sources of noise impact the accuracy of the simulation?

These sources of noise can introduce errors and uncertainties in the simulation, which can affect the accuracy of the final results. For example, atmospheric turbulence can cause fluctuations in the satellite's position, while thermal variations can affect the performance of the satellite's sensors.

4. How can scientists mitigate the effects of noise in geostationary satellite attitude determination simulation?

To mitigate the effects of noise, scientists can use various techniques such as filtering algorithms, error correction methods, and calibration procedures. They can also conduct multiple simulations and average the results to reduce the impact of noise.

5. Are there any ongoing efforts to reduce noise in geostationary satellite attitude determination simulation?

Yes, there are ongoing efforts to reduce noise in these simulations through advancements in technology and techniques. For example, new sensors with higher precision and stability are being developed, and more sophisticated filtering algorithms are being implemented to improve the accuracy of the simulation results.

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