Launching Vehicle Acoustic Data Compression Study Using Lossy Audio Formats

Abstract

The field of data compression has evolved over the last decades. In this way, several techniques to reduce the amount of acquired data from the sensor required to be transmitted have been developed. Those techniques are usually classified by lossless or lossy, where, for the lossless techniques, all acquired data is recovered, while the lossy techniques introduce errors to these data. Each of these techniques presents advantages and drawbacks, being the analyst responsible for choosing the appropriate technique for a specific application. This work presents a comparative study using lossy audio formats to be applied on a launch vehicle on-board acoustic data. The Opus format achieved a higher compression rate in comparison with standard compression techniques by saving up to 254 times the required amount of data to be transmitted through a telemetry link on launcher vehicle, and the lowest discrepancy from original data measured by the mean square error metric.

A Wavelet-Based Steganographic Method for Text Hiding in an Audio Signal

“…Thus, increasing the robustness of the stego-system to compression (reducing redundancy) of the steganocoded audio signal [ 11 , 12 ] subject to the preservation of the integrity of text information (genuine semantic structures), taking into account the features of the psychophysiological model of sound perception (hiding the very fact of text transmission by masking in acoustic signals), is the main objective of this scientific research.…”

“…Thus, using the developed method, it is possible to allow an attacker to re-encode the audio signal with various lossy compression algorithms, but at the same time, the text information embedded in the audio signal maintains integrity. This statement is based on the fact that the current variety of existing compression algorithms [ 9 , 10 , 11 , 12 ] operates according to the same principle, namely, the elimination of the uninformative redundant component of the audio signal. Since the proposed method hides text information at medium frequencies and amplitudes of wavelet coefficients, and because this is its main feature, it can significantly increase the resistance of the stego-system to audio signal compression, taking into account the features of the psychophysiological model of sound perception.…”

Evaluation of lossy compression algorithms using discrete cosine transform for sounding rocket vibration data

“…Examples of works in the lossless framework can be found in [19,20]. Studies proposing lossy compression algorithms can also be found in the literature for telemetry data, see [21][22][23]. For vibration sensors, the works of Mess et al analyze the performance of data compressors using the discrete cosine transform (DCT) and the discrete wavelet transform to encode an 8-bit vibration sensor from ARIANE 5 [24,25].…”