An overview of data acquisition, signal coding and data analysis techniques for MST radars

An overview is given of the data acquisition, signal processing, and data analysis techniques that are currently in use with high power MST/ST (mesosphere stratosphere troposphere/stratosphere troposphere) radars. This review supplements the works of Rastogi (1983) and Farley (1984) presented at previous MAP workshops. A general description is given of data acquisition and signal processing operations and they are characterized on the basis of their disparate time scales. Then signal coding, a brief description of frequently used codes, and their limitations are discussed, and finally, several aspects of statistical data processing such as signal statistics, power spectrum and autocovariance analysis, outlier removal techniques are discussed

Effective Construction of a Class of Bent Quadratic Boolean Functions

In this paper, we consider the characterization of the bentness of quadratic Boolean functions of the form $f(x)=\sum_{i=1}^{\frac{m}{2}-1} Tr^n_1(c_ix^{1+2^{ei}})+ Tr_1^{n/2}(c_{m/2}x^{1+2^{n/2}}) ,$ where $n=me$, $m$ is even and $c_i\in GF(2^e)$. For a general $m$, it is difficult to determine the bentness of these functions. We present the bentness of quadratic Boolean function for two cases: $m=2^vp^r$ and $m=2^vpq$, where $p$ and $q$ are two distinct primes. Further, we give the enumeration of quadratic bent functions for the case $m=2^vpq$

Geometric Capacity Studies for DTV Transmitter Identification By Using Kasami Sequences

The transmitter identification of the DTV systems becomes crucial nowadays. Transmitter identification (TxID, or transmitter fingerprinting) technique is used to detect, diagnose and classify the operating status of any radio transmitter of interest. A pseudo random sequence was proposed to be embedded into the DTV signal before transmission. Thus, the transmitter identification can be realized by invoking the cross-correlation functions between the received signal and the possible candidates of the pseudo random sequences. Gold sequences and Kasami sequences are two excellent candidates for the transmitter ID sequences as they provide a large family of nearly-orthogonal codes. In order to investigate the sensitivity of the transmitter identification in different topologies and Kasami sequences with different length, we present the analysis here for four different geometric layouts, namely circular distribution, doubly concentric and circular distribution, square array and hexagonal tessellation. The covered area and the lowest received signal-to-interference ratio are considered as two essential parameters for the multiple-transmitter identification. It turns out to be that the larger the Kasami sequence length, the larger the received signal-to-interference ratio. Our new analysis can be used to determine the required Kasami sequence length for a specific broadcasting coverage

Unsupervised Learning of Sentence Embeddings using Compositional n-Gram Features

The recent tremendous success of unsupervised word embeddings in a multitude of applications raises the obvious question if similar methods could be derived to improve embeddings (i.e. semantic representations) of word sequences as well. We present a simple but efficient unsupervised objective to train distributed representations of sentences. Our method outperforms the state-of-the-art unsupervised models on most benchmark tasks, highlighting the robustness of the produced general-purpose sentence embeddings.Comment: NAACL 201

Advanced Linear Identification Techniques For Signal Processing And Digital Video Broadcasting

Linear identification technique is to linearly embed a piece of unique information into digital media data for the purpose of satisfying specific demands such as identification, annotation, and copyright, etc. We need to consider the quantity and the quality of identification data to be embedded as well as the corresponding interference to the original subject signal. However, there exist no generalized computationally-efficient optimization techniques for linear identification up to now. Therefore, in this dissertation work, we try to theoretically investigate the advanced linear identification techniques and combat the tradeoff problems between the quality of the embedded identification data and the quality of the subject signal. Two particular signal processing and telecommunication applications, namely transmitter identification and digital watermarking, will be exploited in this work. We propose a novel optimization paradigm for both digital terrestrial television (DTV) systems and multiple digital watermarking systems to maximize the overall signal-to-interference-plus-noise ratio (SINR) over both identification and subject signals. The new theories and practice related to pseudo random sequences, extended arithmetic-geometric mean inequality, and constrained overall system performance are also presented in this dissertation

Digital watermark technology in security applications

With the rising emphasis on security and the number of fraud related crimes around the world, authorities are looking for new technologies to tighten security of identity. Among many modern electronic technologies, digital watermarking has unique advantages to enhance the document authenticity. At the current status of the development, digital watermarking technologies are not as matured as other competing technologies to support identity authentication systems. This work presents improvements in performance of two classes of digital watermarking techniques and investigates the issue of watermark synchronisation. Optimal performance can be obtained if the spreading sequences are designed to be orthogonal to the cover vector. In this thesis, two classes of orthogonalisation methods that generate binary sequences quasi-orthogonal to the cover vector are presented. One method, namely "Sorting and Cancelling" generates sequences that have a high level of orthogonality to the cover vector. The Hadamard Matrix based orthogonalisation method, namely "Hadamard Matrix Search" is able to realise overlapped embedding, thus the watermarking capacity and image fidelity can be improved compared to using short watermark sequences. The results are compared with traditional pseudo-randomly generated binary sequences. The advantages of both classes of orthogonalisation inethods are significant. Another watermarking method that is introduced in the thesis is based on writing-on-dirty-paper theory. The method is presented with biorthogonal codes that have the best robustness. The advantage and trade-offs of using biorthogonal codes with this watermark coding methods are analysed comprehensively. The comparisons between orthogonal and non-orthogonal codes that are used in this watermarking method are also made. It is found that fidelity and robustness are contradictory and it is not possible to optimise them simultaneously. Comparisons are also made between all proposed methods. The comparisons are focused on three major performance criteria, fidelity, capacity and robustness. aom two different viewpoints, conclusions are not the same. For fidelity-centric viewpoint, the dirty-paper coding methods using biorthogonal codes has very strong advantage to preserve image fidelity and the advantage of capacity performance is also significant. However, from the power ratio point of view, the orthogonalisation methods demonstrate significant advantage on capacity and robustness. The conclusions are contradictory but together, they summarise the performance generated by different design considerations. The synchronisation of watermark is firstly provided by high contrast frames around the watermarked image. The edge detection filters are used to detect the high contrast borders of the captured image. By scanning the pixels from the border to the centre, the locations of detected edges are stored. The optimal linear regression algorithm is used to estimate the watermarked image frames. Estimation of the regression function provides rotation angle as the slope of the rotated frames. The scaling is corrected by re-sampling the upright image to the original size. A theoretically studied method that is able to synchronise captured image to sub-pixel level accuracy is also presented. By using invariant transforms and the "symmetric phase only matched filter" the captured image can be corrected accurately to original geometric size. The method uses repeating watermarks to form an array in the spatial domain of the watermarked image and the the array that the locations of its elements can reveal information of rotation, translation and scaling with two filtering processes