kopia lustrzana https://github.com/proto17/dji_droneid
88 wiersze
5.2 KiB
Matlab
88 wiersze
5.2 KiB
Matlab
% Searches through the specified file for the first ZC sequence, and extracts the full bursts (in time)
|
|
%
|
|
% It's very important that the `frequency_offset` be correct such that when applied, the signal is centered at DC (0 Hz)
|
|
% Otherwise the start sample estimate from correlating for the ZC sequence will be off in time as well as the
|
|
% correlation score being lower
|
|
%
|
|
% @param input_path File containing complex 32-bit floating point samples (interleaved I,Q,I,Q,...)
|
|
% @param sample_rate Sample rate that the file was recorded at. Must be an integer multiple of 15.36 MSPS (the minimum
|
|
% sample rate for the DroneID downlink)
|
|
% @param frequency_offset How far off from DC the signal is in the recording (set to 0 for no frequency adjustment)
|
|
% @param correlation_threshold Score on a scale from 0.0 to 1.0 where 1.0 is a perfect match with the ZC sequence. This
|
|
% will determine how closely the recorded ZC sequence must match in order to be extracted
|
|
% as a burst. Usually anywhere from 0.2 to 0.9 are usable values.
|
|
% @param chunk_size How many samples to process at one time. This depends on how much RAM your system has. This value
|
|
% should likely be set > 1e6 but < 20e6. But you do you.
|
|
% @param padding How many additional samples before and after the burst to extract. Must be >= 0
|
|
% @return bursts A matrix where each row contains one burst
|
|
function [bursts] = extract_bursts_from_file(input_path, sample_rate, frequency_offset, correlation_threshold,...
|
|
chunk_size, padding)
|
|
|
|
num_samples = get_sample_count_of_file(input_path);
|
|
|
|
lte_carrier_spacing = 15e3; % OFDM carrier spacing
|
|
fft_size = sample_rate / lte_carrier_spacing; % Number of samples per OFDM symbol (minus cyclic prefix)
|
|
long_cp_len = round(1/192000 * sample_rate); % Number of samples in the long cyclic prefix
|
|
short_cp_len = round(0.0000046875 * sample_rate); % Number of samples in the short cyclic prefix
|
|
|
|
freq_offset_constant = 1j * pi * 2 * (frequency_offset / sample_rate);
|
|
|
|
% The first ZC sequence is the 4th symbol, and the `find_zc_indices_by_file` function will (assuming no major
|
|
% frequency offset) return the sample index of the first sample of the 5th OFDM symbol cyclic prefix. So, back the
|
|
% index off by the number of samples in the first 4 OFDM symbols and their cyclic prefixes
|
|
zc_seq_offset = (fft_size * 4) + long_cp_len + (short_cp_len * 3);
|
|
|
|
% Find all instances of the first ZC sequence
|
|
indices = find_zc_indices_by_file(input_path, sample_rate, frequency_offset, correlation_threshold, chunk_size);
|
|
|
|
% In the DJI Mini 2 there are 9 OFDM symbols: 2 long cyclic prefixes, 7 short. This isn't the case on all drones.
|
|
% For some drones there are just 8 OFDM symbols. It looks like those drones just don't send the first OFDM symbol
|
|
% that's present on the Mini 2. That symbol XOR's out to all zeros anyway, so it's not important. So, to keep
|
|
% things consistent, the logic below will always extract out 9 OFDM symbols worth of samples. In later steps the
|
|
% first OFDM symbol isn't used for anything.
|
|
burst_sample_count = (padding * 2) + (long_cp_len * 2) + (short_cp_len * 7) + (fft_size * 9);
|
|
|
|
% Pre-calculate the frequency offset adjustment vector as this will be constant for all bursts
|
|
freq_offset_vec = reshape(exp(freq_offset_constant * [1:burst_sample_count]), [], 1);
|
|
|
|
% It's not known right away if the first and last bursts are going to be clipped because there aren't enough
|
|
% samples. So, as filthy as it is, use concatenation to build up a list of starting indices that will definitely
|
|
% have all samples present in the input file
|
|
valid_burst_indices = [];
|
|
|
|
for idx=1:length(indices)
|
|
start_index = indices(idx);
|
|
|
|
% Calculate when the burst will start and end
|
|
actual_start_index = start_index - padding - zc_seq_offset;
|
|
actual_end_index = actual_start_index + burst_sample_count;
|
|
|
|
% Ensure that all samples related to this burst are present in the recording
|
|
if (actual_start_index < 1)
|
|
warning("Skipping burst at offset %d as the beginning of the burst has been clipped", start_index);
|
|
continue
|
|
end
|
|
|
|
if (actual_end_index > num_samples)
|
|
warning("Skipping burst at offset %d as the ending of the burst will be clipped", start_index);
|
|
continue
|
|
end
|
|
|
|
% Again, concatenation is filthy, but necessary here since the actual number of bursts is unknown
|
|
valid_burst_indices = [valid_burst_indices actual_start_index];
|
|
end
|
|
|
|
% Now that the true number of bursts is known, create a buffer to hold everything
|
|
bursts = zeros(length(valid_burst_indices), burst_sample_count);
|
|
|
|
for idx=1:length(valid_burst_indices)
|
|
% Read in the current burst. The starting index was calculated above
|
|
burst = read_complex_floats(input_path, valid_burst_indices(idx), burst_sample_count);
|
|
|
|
% Adjust for the user-specified frequency offset that is present in the recording and save those samples off
|
|
bursts(idx,:) = burst .* freq_offset_vec;
|
|
end
|
|
|
|
end
|
|
|