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The main reason why your Kalman filter is not working is because you are not converting lat and lon values to kms. In the code below, I defined a new function called lat_lon_posx_posy which converts lat and lon values to px and py values in mts. You will need to make the following changes to your code. Include the following function import utm def ...


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First of all, sampling frequency and sampling rate are synonymous. You mean sampling frequency of 44.1 kHz with a data length of 20 ms. Second of all, 20 ms of data at 44.1 kHz will give you 882 points. Not enough for a 1024-point FFT. You will either need to upsample to 51.2 kHz, that way 20 ms will give you 1024 points. Or you could append 142 zeroes to ...


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I will contribute to this question from my area of experience, which is in speech enhancement. For noise suppression, you can use classical speech enhancement algorithms (spectral subtraction, wiener filtering, etc) but they mostly introduce artefacts in the enhanced speech. Additionally, there are also machine learning approaches which you can try. I am ...


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You can model your system as a linear time varying, where only the measurement matrix $H_k$ varies in time \begin{align} x_{k+1} &= F\,x_k, \\ y_k &= H_k\,x_k. \end{align} Namely in your case you can consider $y_k^i=H^i\,x_k$ ($i$ is just an index, not a power) to be the output of the $i$th sensor. So at a time $k$ when only sensor 1 is active you ...


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In either Overlap-add or Overlap-save, the FFT is doing the Discrete-Fourier Transform that periodically extends your input data. The DFT does only circular convolution, so you need to make this tool that does circular convolution into a tool that does linear convolution. And Overlap-add and Overlap-save are an adaptation of a circular convolver to do the ...


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Interpolating discontinuous waveforms is usually not a good idea. The way I would approach your problem would be to recognize your signals as pulse trains. So I would assume that the convolution a single pulse from one waveform with a single pulse from the other waveform was also a pulse. so signals A and B could be represented as a train of continuous ...


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