Suppose we have two sensors which are close to each other and the first has its own measured signal value, how this sensor can have an idea, margin or estimate of the signal measured by the second sensor in the proximity, knowing that these sensors does not know the original signal power emitted by the station or physical phenomenon. Obviously, I am not asking for the solution where the second can send the measured value to the first sensor.
Thanks in advance
Dear Kassem,
The problem you search for its solution is one of prediction. Also, extrapolation and interpolation. To apply these methods, one sample is not sufficient to make any decision on the neighboring values. At least two samples are required to estimate the nearby sample. As the number of the samples increases the estimation will be more close to the real value. The simplest method is the linear interpolation and extrapolation and it works well when the samples get closer to each other. This depends on approximating any curve in a short interval by a piece of a straight line.
Dear Abdelhalim,
Thank you for your response. The 'Single' value I have is a summary statistic of M samples so in practice I have M samples and not only one. Please can you suggest any paper for linear interpolation/extrapolation that's dealing with this problem.
Thanks in advance
Dear Kassem,
There are many literature about interpolation and extrapolation as a numerical techniques. You can see the Link:http://pjl.ucalgary.ca/courses/physics481/computational-physics/Ouyed-Chapter-4-Interpolation-Extrapolation-Techniques.pdf
For more information you need only to search the web with the key words: Interpolation and extrapolation.
These functions are also included in Mathlab help files.
wish you success
What type of information is known by each sensor about the other(s)?
each node know the location of the others. Or similarly, the distance between the sensors is known. Also, the sensors are identical.
Alright. Any assumptions about the location of the primary signal source?
No. The assumption is that its location is unknown to all sensors. From your questions I see, may be you got what I want correctly. Thanks
That's interesting. I have come across similar problems that were addressed theoretically using stochastic geometry tools. Of course, such method require many assumptions which I guess is not the case in your situation. I'll let you know if anything comes to mind in this regard and I appreciate if you keep me updated whenever you find a convincing answer.
Thanks,
Omar
Use TDMA based multiplexing for process these two signals. Use synchronization pulse for the end of transmission. Then it is easy to estimate the two different sources
Thank you
all the best
I believe I found a case that matches your needs. Check Section 10.5 of:
http://www.lopezbenitez.es/thesis/PhDThesis_LopezBenitez.pdf
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