Radiometric identification is the problem of attributing a signal to a specific source. In this work, a radiometric identification algorithm is developed using the whitening transformation. The ...approach stands out from the more established methods in that it works directly on the raw IQ data and hence is featureless. As such, the commonly used dimensionality reduction algorithms do not apply. The premise of the idea is that a data set is "most white" when projected on its own whitening matrix than on any other. In practice, transformed data are never strictly white since the training and the test data differ. The Förstner-Moonen measure that quantifies the similarity of covariance matrices is used to establish the degree of whiteness. The whitening transform that produces a data set with the minimum Förstner-Moonen distance to a white noise process is the source signal. The source is determined by the output of the mode function operated on the Majority Vote Classifier decisions. Using the Förstner-Moonen measure presents a different perspective compared to maximum likelihood and Euclidean distance metrics. The whitening transform is also contrasted with the more recent deep learning approaches that are still dependent on feature vectors with large dimensions and lengthy training phases. It is shown that the proposed method is simpler to implement, requires no features vectors, needs minimal training and because of its non-iterative structure is faster than existing approaches.
The range resolution of radar is inversely proportional to the swept bandwidth. However, this bandwidth may not be available due to a variety of reasons, including spectrum congestion and lack of ...instantaneous bandwidth despite access to a larger tunable bandwidth. Existing approaches to achieving high-range resolution include bandwidth extrapolation, ultrawideband coherent processing, and spectral splicing of narrowband stepped-frequency pulses. In this article, we achieve high-range resolution of a wideband chirp from a sequence of narrowband pulses using coherent-phase extension of the beat tones of an FMCW dechirper. By phase matching the beat tones across pulse boundaries, the algorithm trades a longer observation interval for a smaller swept bandwidth. Phase matching of the short beat tones is applied in two steps to first obtain the coarse estimate of the beat frequencies which are then used as the starting point in the formation of the range-Doppler map that now enjoys the two-dimensional fast-Fourier transform (2-D-FFT) gain. With this approach, a fraction of the total bandwidth to obtain a range resolution of a wideband chirp is used. Using both simulations and experimental data, the proposed high-resolution algorithm is applied to a narrowband chirp sequence with bandwidth <inline-formula><tex-math notation="LaTeX">B</tex-math></inline-formula> to generate range-Doppler maps with range resolution corresponding to a wideband chirp sequence of bandwidth <inline-formula><tex-math notation="LaTeX">NB</tex-math></inline-formula>.
Range-Doppler estimation algorithms that use the phase of the returned signal face the 2<inline-formula><tex-math notation="LaTeX">\pi</tex-math></inline-formula> phase ambiguity problem. In this ...letter, we eliminate phase wrapping by using two coincident opposite polarity chirps but equal starting frequencies. The returns for both chirps from the same target have near equal phases. The phase wrap is present in both returns but they are the same. Therefore, the differential phase matching used to pair the returns from the same target cancels out the phase wrap. No phase unwrapping is needed. The proposed method has no inherent maximum unambiguous range or velocity, works in multitarget theaters, requires a much lower sampling rate, is not affected by range migration, decouples the Doppler cycle from the pulse repetition frequency and is computationally more efficient than FFT-based methods.
An analysis of the relationship between multipath ghosts and the direct target image for radar imaging is presented. A multipath point spread function (PSF) is defined that allows for specular ...reflections in the local environment and can allow the ghost images to be localized. Analysis of the multipath PSF shows that certain ghosts can only be focused for the far field synthetic aperture radar case and not the full array case. Importantly, the ghosts are shown to be equivalent to direct target images taken from different observation angles. This equivalence suggests that exploiting the ghosts would improve target classification performance, and this improvement is demonstrated using experimental data and a naïve Bayesian classifer. The maximum performance gain achieved is 32%.
A through-the-wall radar image (TWRI) bears little resemblance to the equivalent optical image, making it difficult to interpret. To maximize the intelligence that may be obtained, it is desirable to ...automate the classification of targets in the image to support human operators. This paper presents a technique for classifying stationary targets based on the high-range resolution profile (HRRP) extracted from 3-D TWRIs. The dependence of the image on the target location is discussed using a system point spread function (PSF) approach. It is shown that the position dependence will cause a classifier to fail, unless the image to be classified is aligned to a classifier-training location. A target image alignment technique based on deconvolution of the image with the system PSF is proposed. Comparison of the aligned target images with measured images shows the alignment process introducing normalized mean squared error (NMSE) ≤ 9%. The HRRP extracted from aligned target images are classified using a naive Bayesian classifier supported by principal component analysis. The classifier is tested using a real TWRI of canonical targets behind a concrete wall and shown to obtain correct classification rates ≥97%.
In the crowded underwater acoustic channels, the ability to recognize sonar transmissions based on an identifying signature is quite valuable. In this work, we propose an algorithm to embed a ...watermark in the time-frequency coefficients of a sonar waveform and produce a watermarked sonar. The watermark, which is a digital signature, is used to authenticate the sonar by verifying the source that is broadcasting the waveform. The embedding rule is modeled after spread spectrum modulation and driven by two secure keys. The first key consists of the spreading code that is unique to each source. The second key is an embedding mask used to select and additively modify the selected time-frequency cells of the sonar. The mask is chosen based on the frequency response of the acoustic channel (primarily, its time and frequency coherence) and the signal energy distribution in the time-frequency plane. The detector is modeled after a matched filter receiver performing a replica correlation with the spread watermark passed through the channel model. A successful detection needs access to both the spreading code and the embedding mask. Watermark detection performance is extensively evaluated based on range; watermark energy; watermark placement; ambient noise; number of multipaths; and other ocean parameters, such as depth, surface, and bottom models.
Data Embedding in JPEG Bitstream by Code Mapping Mobasseri, Bijan G.; Berger, Robert J.; Marcinak, Michael P. ...
IEEE transactions on image processing,
04/2010, Volume:
19, Issue:
4
Journal Article
Peer reviewed
We propose an algorithm to embed data directly in the bitstream of JPEG imagery. The motivation for this approach is that images are seldom available in uncompressed form. Algorithms that operate in ...spatial domain, or even in coefficient domain, require full (or at best) partial decompression. Our approach exploits the fact that only a fraction of JPEG code space is actually used by available encoders. Data embedding is performed by mapping a used variable length code (VLC) to an unused VLC. However, standard viewers unaware of the change will not properly display the image. We address this problem by a novel error concealment technique. Concealment works by remapping run/size values of marked VLCs so that standard viewers do not lose synchronization and displays the image with minimum loss of quality. It is possible for the embedded image to be visually identical to the original even though the two files are bitwise different. The algorithm is fast and transparent and embedding is reversible and file-size preserving. Under certain circumstances, file size may actually decrease despite carrying a payload.
Constellation diagram is a traditional and powerful tool for design and evaluation of digital modulations. In this work we propose to use constellation shape as a robust signature for digital ...modulation recognition. We represent the transmitted “information” by the geometry of the constellation. Received information is in turn the recovered constellation shape that is deformed by noise, channel and receiver implementation. We first demonstrate that
fuzzy c-means clustering is capable of robust recovery of the unknown constellation. To perform Bayesian inference, the reconstructed constellation is modeled by a discrete multiple-valued nonhomogenous spatial random field. For candidate modulations, their corresponding random fields are modeled off-line. The unknown constellation shape is then classified by an ML rule based on the preceding model building phase. The algorithm is applicable to digital modulations of arbitrary size and dimensionality.
Das Konstellationsdiagramm ist ein traditionelles und leistungsfähiges Werkzeug für den Entwurf und die Bewertung digitaler Modulationsverfahren. In dieser Arbeit schlagen wir vor, die Konstellationsform als robuste Signatur zur digitalen Modulationserkennung zu verwenden. Wir stellen die übertragene “Information” durch die Geometrie der Konstellation dar. Die empfangene Information ist dann die rekonstruierte Konstellationsform, welche durch Rauschen, den Kanal und die Empfängerimplementierung deformiert ist. Zunächst demonstrieren wir, daßeine Gruppenbildung mittels fuzzy c-Mittelwerten in der Lage ist, die unbekannte Konstellation robust zu rekonstruieren. Um Bayessche Schlußfolgerungen durchführen zu können, wird die rekonstruierte Konstellation durch ein diskretes, mehrwertiges, nichthomogenes räumliches Zufallsfeld modelliert. Die den in Frage kommenden Modulationen entsprechenden Zufallsfelder werden im voraus modelliert. Die unbekannte Konstellationsform wird dann mittels einer ML-Regel klassifiziert, welche auf der vorhergenhenden Modellierungsphase beruht. Der Algorithmus eignet sich für digitale Modulationsverfahren beliebiger Größe und Dimensionalität.
Un diagramme de constellation est un outil traditionnel et puissant de conception et d'évaluation d'une modulation numérique. Dans ce travail, nous proposons l'utilisation de la forme de constellation comme signature robuste pour la reconnaissance de modulations numériques. Nous représentons l'information transmise par la géométrie de la constellation. A son tour, l'information reçue est constituée par la forme de la constellation. qui est déformée par le bruit, le canal et l'implémentation du récepteur. Nous démontrons tout d'abord qu'un clustering par l'algorithme c-means flou est capable de retrouver de façon robuste une constellation inconnue. Pour effectuer une inférence Bayésienne, la constellation reconstruite est modélisée par un champ aléatoire spatial non-homogène à valeurs multiples discrètes. Pour les modulations candidates, leurs champs aléatoires correspondants sont modélisés horsligne. La forme de constellation inconnue est ensuite classifiée par une règle ML basée sur la phase précédente de construction du modèle. L'algorithme est applicable à des modulations numériques de taille et de dimensionnalité arbitraires.
U radu je predložena procedura za umetanje vodenog žiga u sliku i kompresiju slike zasnovana na Hermitovoj projekcijskoj metodi. Odgovarajući koeficijenti, dobiveni kao rezultat primjene razvoja ...slike u red Hermitovih funkcija, korišteni su za umetanje vodenog žiga watermark). S obzirom na to da se slika može efikasno rekonstruirati korištenjem znatno manjeg broja Hermitovih koeficijenata u odnosu na broj originalnih koeficijenata slike, umetanje vodenog žiga zapravo je provedeno u domeni kompresije, uz očuvanje visoke kvalitete slike (velika vrijednost PSNR). Učinkovitost predložene procedure ispitana je eksperimentalno i pokazuje značajnu otpornost na uobičajene napade. Osim uobičajenih, procedura pokazuje robusnost i na geometrijske napade. Predloženi pristup može biti korišten u različitim aplikacijama za zaštitu autorskih prava, naročito u aplikacijama koje ujedno zahtijevaju i kompresiju slike, kao što su multimedijske i internetske aplikacije, daljinsko očitavanje podataka i satelitska snimanja.
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