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Compressive Sensing Based Algorithms for Electronic Defence by Amit Kumar Mishra, Ryno Strauss Verster

By Amit Kumar Mishra, Ryno Strauss Verster

This e-book info a few of the significant advancements within the implementation of compressive sensing in radio functions for digital safety and battle verbal exchange use. It presents a finished historical past to the topic and while describes a few novel algorithms. It additionally investigates program worth and performance-related parameters of compressive sensing in situations resembling course discovering, spectrum tracking, detection, and classification.

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Extra resources for Compressive Sensing Based Algorithms for Electronic Defence

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Existing transform bases such as the discrete Fourier transform (DFT) does not comply with the CS basis criteria, which is a problem for our investigation as the DFT is pivotal to our digital processing goals. However, when a DFT is operated on by an iid Gaussian matrix it results in an overall matrix that does comply with the CS basis criteria. This result is further discussed in a later section, but it is important to note that other discrete transforms such as DCT, WHT, etc. use the same operation with an iid Gaussian matrix to achieve CS basis compliance.

E. RWR systems), as they are primarily pulsed [88]. Nevertheless, the process remains similar, although the features assigned to signals differ. e. deinterleaving) are: • • • • • Signal classification Frequency of operation RF bandwidth Modulation type Power Levels. The features assigned to a particular signal are transformed into a digital word, which is then passed onto the clustering analysis process based on a knowledgebased algorithm which is mostly a histogram analysis method [88] (see Fig.

In [182] a seminal prototype of an NUS IC device was developed, using commercially off-the shelf components (COTS) for quantization and recovery of signal from 800 MHz to 2 GHz sub-Nyquist sampling, using a 14 bit 400 MHz ADC. NUS relies on selecting, at random, integer multiples of the underlying Nyquist rate allowing for corrective calibration, comparatively different to the random unrelated Nyquist sampling technique used by [91]. e. 4 GHz), allows the NUS architecture to select and hold samples at random, conditioned on the PRBS.

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