An introduction to the interim digital SAR processor and the characteristics of the associated Seasat SAR imagery

Basic engineering data regarding the Interim Digital SAR Processor (IDP) and the digitally correlated Seasat synthetic aperature radar (SAR) imagery are presented. The correlation function and IDP hardware/software configuration are described, and a preliminary performance assessment presented. The geometric and radiometric characteristics, with special emphasis on those peculiar to the IDP produced imagery, are described

Mismatched Filter Effects on Synthetic Aperture Radar Image Quality Metrics

Detection of targets across a wide dynamic range is an enduring challenge in radar. This work formulates a modified least-squares mismatched filter that greatly reduces these sidelobes in order to enable the detection of small radar cross section targets in the presence of considerably larger scatterers, increasing the dynamic range. Unlike previous mismatched filters, the proposed filter is applicable to noisy, oversampled signals with no requirements on signal structure. Range profiles and images are presented to demonstrate the superior sidelobe suppression of the modified least-squares mismatched filter in comparison to the commonly employed matched filter. Various weighting vectors are introduced to further increase sidelobe suppression for particular scene geometries. The modified mismatched filter created with the addition of a noise compensation term is shown to have superior sidelobe suppression to that of the matched filter across all signal-to-noise ratios, coming at the relatively low expense of a small degree of mainlobe energy loss and widening, as well as increased processing time

Hardware Implementation of Filtering Based Sidelobe Suppression for Spectrally Agile Multicarrier based Cognitive Radio Systems

Due to the ever increasing dependency on existing wireless technologies and the growing usage of sophisticated wireless devices, the demand for bandwidth is rising exponentially. Also, the Federal Communications Commission (FCC) has reserved a considerable amount of spectrum for licensed users. As a result, the unlicensed spectrum usage is constrained to the overcrowded unlicensed spectrum. Various spectral management surveys have indicated inefficient spectrum utilization in the licensed spectral bands. The congested unlicensed spectrum and inefficiently used licensed frequency bands calls for an approach to use the available spectrum opportunistically. Therefore, the concept of Spectrum Pooling , which is based on Dynamic Spectrum Access (DSA), was proposed to make the unused sections of licensed spectrum available to the unlicensed users. In Spectrum Pooling, an empty section of licensed spectrum is borrowed by a secondary user for certain period of time without interfering with the licensed user. Orthogonal Frequency Division Multiplexing (OFDM) is a transmission scheme that is a candidate for Spectrum Pooling since it is capable of forming an adaptive spectral shape that allows coexistence of licensed and unlicensed users while attemting to minimize any interference. Subcarriers in the OFDM signal can be deactivated to generate Non-Contiguous OFDM (NC-OFDM). Even though NC-OFDM allows efficient use of available spectrum, it causes out of band (OOB) radiation, which adversely affects the performance of adjacent user. This thesis presents two novel techniques for combat the effects of OOB radiation generated by NC-OFDM. The proposed techniques employ a filtering-based approach combined with the technique of windowing in order to suppress the unwanted sidelobes by around 35dB-40dB. The attenuation is achieved without affecting other transmission parameters of the secondary user significantly

Sidelobe Suppression and Agile Transmission Techniques for Multicarrier-based Cognitive Radio Systems

With the advent of new high data rate wireless applications, as well as growth of existing wireless services, demand for additional bandwidth is rapidly increasing. Existing spectrum allocation policies of the Federal Communications Commission (FCC) prohibits unlicensed access to licensed spectrum, constraining them instead to several heavily populated, interference-prone frequency bands, which causes spectrum scarcity. However, it has been shown by several spectrum measurement campaigns that the current licensed spectrum usage across time and frequency is inefficient. Therefore, a concept of unlicensed users temporarily ``borrowing spectrum from incumbent license holders to improve the spectrum utilization, called ``spectrum pooling , which is based on dynamic spectrum access (DSA), is proposed. Cognitive radio is a communication paradigm that employs software-defined radio technology in order to perform DSA and offers versatile, powerful and portable wireless transceivers. Orthogonal frequency division multiplexing (OFDM) is a promising candidate for cognitive radio transmission. OFDM supports high data rates that are robust to channel impairments. In addition, some subcarriers can be deactivated which constitutes a non-contiguous OFDM (NC-OFDM) transmission. However, one of the biggest problems for OFDM transmission is high out-of-band (OOB) radiation, which is caused by sinc-type function representing the symbols during one time constant. Thus, high sidelobe may occur that will interfere with neighboring transmissions. This thesis presents two novel techniques for NC-OFDM sidelobe suppression. Another concern about cognitive radio systems is that the influence of frequency-selective fading channel. Consequently, this thesis also presents a combined approach employing power loading, bit allocation and sidelobe suppression for OFDM-based cognitive radio systems optimization

Automatic Partial Extraction from the Modal Distribution

The Modal Distribution (MD) is a time-frequency distribution specifically designed to model the quasi-harmonic, multi-sinusoidal, nature of music signals and belongs to the Cohen general class of time-frequency distributions. The problem of signal synthesis from bilinear time-frequency representations such as the Wigner distribution has been investigated [1,14] us-ing methods which exploit an outer-product interpretation of these distributions. Methods of synthesis from the MD based on a sinusoidal-analysis-synthesis procedure using estimates of in-stantaneous frequency and amplitude values have relied on a heuristic search ‘by eye’ for peaks in the time-frequency domain [2,7,8]. An approach to detection of sinusoidal components with the Wigner Distribution has been investigated in [15] based on a comparison of peak magnitudes with the DFT and STFT. In this paper we propose an improved frequency smoothing kernel for use in MD partial tracking and adapt the McCauley-Quatieri sinusoidal analysis procedure to enable a sum of sinusoids synthe-sis. We demonstrate that the improved kernel enhances automatic partial extraction and that the MD estimates of instantaneous amplitude and frequency are preserved. Suggestions for future extensions to the synthesis procedure are given

Spectrum Adaptation in Cognitive Radio Systems with Operating Constraints

The explosion of high-data-rate-demanding wireless applications such as smart-phones and wireless Internet access devices, together with growth of existing wireless services, are creating a shortage of the scarce Radio Frequency (RF) spectrum. However, several spectrum measurement campaigns revealed that current spectrum usage across time and frequency is inefficient, creating the artificial shortage of the spectrum because of the traditional exclusive command-and-control model of using the spectrum. Therefore, a new concept of Cognitive Radio (CR) has been emerging recently in which unlicensed users temporarily borrow spectrum from the licensed Primary Users (PU) based on the Dynamic Spectrum Access (DSA) technique that is also known as the spectrum sharing concept. A CR is an intelligent radio system based on the Software Defined Radio platform with artificial intelligence capability which can learn, adapt, and reconfigure through interaction with the operating environment. A CR system will revolutionize the way people share the RF spectrum, lowering harmful interference to the licensed PU of the spectrum, fostering innovative DSA technology and giving people more choices when it comes to using the wireless-communication-dependent applications without having any spectrum congestion problems. A key technical challenge for enabling secondary access to the licensed spectrum adaptation is to ensure that the CR does not interfere with the licensed incumbent users. However, incumbent user behavior is dynamic and requires CR systems to adapt this behavior in order to maintain smooth information transmission. In this context, the objective of this dissertation is to explore design issues for CR systems focusing on adaptation of physical layer parameters related to spectrum sensing, spectrum shaping, and rate/power control. Specifically, this dissertation discusses dynamic threshold adaptation for energy detector spectrum sensing, spectrum allocation and power control in Orthogonal Frequency Division Multiplexing-(OFDM-)based CR with operating constraints, and adjacent band interference suppression techniques in turbo-coded OFDM-based CR systems

Underwater Acoustic Imaging: One-bit Digitisation

In underwater acoustic imaging (UAI), the combination of a two-dimensional (2-D) array and replicate correlation can produce 3-D images, typically of objects at a range of 2 m. A system already developed achieves the high data acquisition rate needed through one-bit sampling (sensing only the sign of the received signal). Noise added before the one-bit sampling avoids the production of 'ghosts' in the image. By simulation and mathematical analysis, the effects of one-bit and added noise are studied for a chirp signal, with a restriction so far to 1-D images (image amplitude versus range). Conditions are given for the avoidance of ghosts and the minimisation of 'image noise' - noise in the image due to one-bit and added noise. A model of image noise is proposed, which is corroborated by the tests carried out to date. A general formula for the root-mean-square image noise is obtained. It has previously been suggested that filtering the singal after sampling would improve the image. However, it is shown that filtering is unnecessary and indeed makes the image worse. It is shown that a strong target can suppress evidence of a weak target because, when the strength of the return signal is raised, essentially the amplitude of the added noise must be raised to avoid 'ghosts'. A general formula, giving the ratio of target strengths such that the weak target has a 50% probability of detection, is obtained