Coherent versus incoherent averaging of data

In summary: However, the downside is that some information is lost in the process. The reason for using these averaging methods is to reduce noise and improve the quality of the image.
  • #1
EightBall
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I'm doing an assignment for the course Earth Observation. one of the questions is to plot an image in Matlab. you are given 5 data files containing each a 2400x2000 matrix with complex values at each matrix element. these 5 data files can be transformed into 5 images since each data file is in fact an image of the same place on Earth taken at a different time. the goal now is to combine these 5 images into 1 image by the means of averaging. this has to be done on two ways: coherent averaging and incoherent averaging. in the assignment is explained how you should do the averaging, but what the assignment does not tell is what it exactly does to your data and why it is done that way. now I've applied the two averaging methods and i get 2 images. the one made with coherent averaging does not look different from the 5 images that were combined. The image obtained through incoherent averaging however does look a lot sharper (less speckles). now the question of the assignment is not only what is the difference, but also why is there a difference? this is also the question i want to ask you. Because i don't understand what the difference is between coherent and incoherent averaging or what it does and why it does what it does, i can't answer the question of the assignment



what the assignment says about coherent and incoherent averaging is the following:
'For coherent averaging, the real and the imaginary parts of the radar signals are summed
separately, and later combined into complex numbers, resulting in a coherent average.
For the incoherent average, only the absolute values of the complex data are summed,
disregarding the phase information.'




I've tried to search the internet about these averaging methods. I only found out that incoherent averaging 'destroys' in some way the phase information of the data. but this didn't made me any wiser.

thanks in advance for your time and help.
 
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  • #2
The difference between coherent and incoherent averaging lies in the way that the data is treated when it is combined. In coherent averaging, the real and imaginary parts of the data are averaged separately and then combined into a single value. This preserves the phase information of the original data, which means that the resulting image will have a similar appearance to the original images. In incoherent averaging, the absolute values of the complex data are summed and the phase information is discarded. This leads to a sharper image since the noise is reduced by the averaging process.
 

1. What is the difference between coherent and incoherent averaging of data?

Coherent averaging involves combining multiple measurements of the same signal that are in phase with each other, resulting in a stronger and more accurate signal. Incoherent averaging, on the other hand, combines measurements that are out of phase, resulting in a weaker and less accurate signal.

2. When should I use coherent averaging versus incoherent averaging?

Coherent averaging is typically used when the signal being measured is relatively stable and consistent, while incoherent averaging is used when the signal is noisy or changing rapidly. Coherent averaging requires a synchronized measurement setup, while incoherent averaging can be done with unsynchronized measurements.

3. How does coherent averaging improve the accuracy of data?

Coherent averaging helps to reduce random noise in the data by combining multiple measurements that are all in phase with each other. This results in a stronger and more precise signal, making the data more accurate.

4. Are there any disadvantages to using incoherent averaging?

One major disadvantage of incoherent averaging is that it can amplify any systematic errors or biases in the data. This can result in inaccurate measurements and should be taken into consideration when choosing which averaging method to use.

5. Can I use a combination of coherent and incoherent averaging?

Yes, it is possible to use a combination of both coherent and incoherent averaging in certain situations. This is known as hybrid averaging and is often used in situations where the signal being measured is both stable and noisy. It can provide the benefits of both methods while minimizing their disadvantages.

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