Moving and stationary target acquisition radar image enhancement through polynomial windows

The Fourier transform involved in synthetic aperture radar (SAR) imaging causes undesired sidelobes which obscure weak backscatters and affect the image clarity. These sidelobes can be suppressed without deteriorating the image resolution by smoothing functions known as windowing or apodization. Recently, the theory of orthogonal polynomials has gained considerable attention in signal processing applications. The window functions that are derived from the orthogonal polynomials have interesting sidelobe roll-off properties for better sidelobe apodization, hence it can be used for radar image enhancement. In this work, a new window is constructed from Jacobi orthogonal polynomials and its performance in SAR imaging is analyzed and compared with commonly used window functions. Also, apodization functions involved in Fourier transform harmonic analysis and Fourier transform spectroscopy are discussed in the context of SAR imaging

On the performance of superposition window

Superposition window is often used in the digital signal processing and other fields of signal processing such as power spectral estimation and adaptive time-frequency analysis. Different overlap and windows used in superposition system may affect the final results. The main contribution of this paper is in providing the insight into the properties of the overlap-add technique with different window or overlap ratio, which is very helpful in selecting these parameters for a practical application

Reconfigurable Architecture of UFMC Transmitter for 5G and Its FPGA Prototype

[EN] A universal-filtered multicarrier (UFMC) system that is a generalization of filtered orthogonal frequency-division multiplexing (OFDM) and filter-bank-based multicarrier is being considered as a potential candidate for fifth-generation due to its robustness against intercarrier interference as in cyclic-prefix-based OFDM systems. However, real-time hardware realization of multicarrier systems is limited by a large number of arithmetic units for inverse fast Fourier transform and pulse-shaping filters. In this paper, we aim to propose a low-complexity and reconfigurable architecture for a baseband UFMC transmitter. To the best of our knowledge, the proposed architecture is the first reconfigurable architecture that has the flexibility to choose the number of subcarriers in a subband without any change in hardware resources. In addition, the proposed architecture selects the filter from a group of filters with a single selection line. Moreover, we use a commercially available field-programmable gate array device for real-time testing and analyzing the baseband UFMC signal. From the extensive experiments, we study the occupied bandwidth, main-lobe power, and sidelobe power of the baseband signal with different filters in real-time scenarios. Finally, we measure the quantization error in baseband signal generation for the proposed UFMC transmitter architecture and find comparable with the error bound.Kumar, V.; Mukherjee, M.; Lloret, J. (2020). Reconfigurable Architecture of UFMC Transmitter for 5G and Its FPGA Prototype. IEEE Systems Journal. 14(1):28-38. https://doi.org/10.1109/JSYST.2019.2923549S283814

Adaptive beamforming and switching in smart antenna systems

The ever increasing requirement for providing large bandwidth and seamless data access to commuters has prompted new challenges to wireless solution providers. The communication channel characteristics between mobile clients and base station change rapidly with the increasing traveling speed of vehicles. Smart antenna systems with adaptive beamforming and switching technology is the key component to tackle the challenges. As a spatial filter, beamformer has long been widely used in wireless communication, radar, acoustics, medical imaging systems to enhance the received signal from a particular looking direction while suppressing noise and interference from other directions. The adaptive beamforming algorithm provides the capability to track the varying nature of the communication channel characteristics. However, the conventional adaptive beamformer assumes that the Direction of Arrival (DOA) of the signal of interest changes slowly, although the interference direction could be changed dynamically. The proliferation of High Speed Rail (HSR) and seamless wireless communication between infrastructure ( roadside, trackside equipment) and the vehicles (train, car, boat etc.) brings a unique challenge for adaptive beamforming due to its rapid change of DOA. For a HSR train with 250km/h, the DOA change speed can be up to 4⁰ per millisecond. To address these unique challenges, faster algorithms to calculate the beamforming weight based on the rapid-changing DOA are needed. In this dissertation, two strategies are adopted to address the challenges. The first one is to improve the weight calculation speed. The second strategy is to improve the speed of DOA estimation for the impinging signal by leveraging on the predefined constrained route for the transportation market. Based on these concepts, various algorithms in beampattern generation and adaptive weight control are evaluated and investigated in this thesis. The well known Generalized Sidelobe Cancellation (GSC) architecture is adopted in this dissertation. But it faces serious signal cancellation problem when the estimated DOA deviates from the actual DOA which is severe in high mobility scenarios as in the transportation market. Algorithms to improve various parts of the GSC are proposed in this dissertation. Firstly, a Cyclic Variable Step Size (CVSS) algorithm for adjusting the Least Mean Square (LMS) step size with simplicity for implementation is proposed and evaluated. Secondly, a Kalman filter based solution to fuse different sensor information for a faster estimation and tracking of the DOA is investigated and proposed. Thirdly, to address the DOA mismatch issue caused by the rapid DOA change, a fast blocking matrix generation algorithm named Simplifized Zero Placement Algorithm (SZPA) is proposed to mitigate the signal cancellation in GSC. Fourthly, to make the beam pattern robust against DOA mismatch, a fast algorithm for the generation of at beam pattern named Zero Placement Flat Top (ZPFT) for the fixed beamforming path in GSC is proposed. Finally, to evaluate the effectiveness and performance of the beamforming algorithms, wireless channel simulation is needed. One of the challenging aspects for wireless simulation is the coupling between Probability Density Function (PDF) and Power Spectral Density (PSD) for a random variable. In this regard, a simplified solution to simulate Non Gaussian wireless channel is proposed, proved and evaluated for the effectiveness of the algorithm. With the above optimizations, the controlled simulation shows that the at top beampattern can be generated 380 times faster than iterative optimization method and blocking matrix can be generated 9 times faster than normal SVD method while the same overall optimum state performance can be achieved

Ultra low range sidelobe level pulse compression waveform design for spaceborne meteorological radars.

Meteorological measurements from spaceborne radars present several advantages over current passive techniques, due to the radar capability to discriminate backscattered energy in range. However, the system configuration imposes stringent design requirements in order to guarantee cloud and rain detectability, in particular on the radar waveform. Since power is severely restricted on board a satellite, it is necessary to achieve an efficient range resolution with low transmitted power requirements. Pulse compression theory solves the previous conflicting demand, but the transmitted signal needs to be carefully designed in order to allow the significantly large dynamic range (between 60 and 80 dB depending on the type of meteorological target) needed to carry out the measurements. Several pulse compression range sidelobe reduction techniques of differing natures have been investigated and reported in the literature during the past 50 years. A detailed survey of the most relevant range sidelobe supression procedures has been carried out in order to identify the most suitable frequency modulation candidates which are potentially capable of meeting the stringent specifications of spaceborne radar meteorology. Novel pulse compression waveform design techniques have also been developed, employing linear FM predistortion functions and asymmetric frequency modulation laws, which provide excellent performance in terms of range sidelobe level (below -60 dB) and Doppler tolerance. Different options for the provision of a rain mode for the RA-2 Radar Altimeter (due to fly on European Space Agency ENVISAT satellite) are described, based on altimetry linear FM full-deramp technique concepts. Finally, amplitude modulated pulse compression waveform design alternatives are analysed for the MACSIM radar (Millimetre wave Active Cloud Structure Imaging Mission, European Space Agency Pre Phase A Study), which allow to measure different type of clouds within the Mission required radiometric resolution accuracy

Subcarrier Filtering For Spectrally Efficient Multicarrier Modulation Schemes and Its Impact on PAPR: A Unified Approach

Multicarrier modulation (MCM) based schemes have been a major contributing factor in revolutionizing cellular networks due to their ability to overcome fading. One of the popular scheme orthogonal frequency division multiple access (OFDMA), having been part of 4G, is also adapted as part of 5G enhanced mobile broadband (eMBB).  Though it has several advantages, spectral efficiency (SE) and peak to average power ratio (PAPR) have been two major concerns which have attracted lot of attention resulting in proposals of several other MCM schemes.  But most of these studies have treated the two issues independently. This paper in particular studies the subcarrier filtering approach to improve the spectral efficiency of MCM scheme and its impact on the overall PAPR of such schemes. The analysis shows that the PAPR improvement is also achieved by such filters meant for spectral confinement and the simulation results validate the same provoking a unified research direction less explored till now

Bathymetric Artifacts in Sea Beam Data: How to Recognize Them and What Causes Them

Sea Beam multibeam bathymetric data have greatly advanced understanding of the deep seafloor. However, several types of bathymetric artifacts have been identified in Sea Beam\u27s contoured output. Surveys with many overlapping swaths and digital recording on magnetic tape of Sea Beam\u27s 16 acoustic returns made it possible to evaluate actual system performance. The artifacts are not due to the contouring algorithm used. Rather, they result from errors in echo detection and processing. These errors are due to internal factors such as side lobe interference, bottom-tracking gate malfunctions, or external interference from other sound sources (e.g., 3.5 kHz echo sounders or seismic sound sources). Although many artifacts are obviously spurious and would be disregarded, some (particularly the omega effects described in this paper) are more subtle and could mislead the unwary observer. Artifacts observed could be mistaken for volcanic constructs, abyssal hill trends, hydrothermal mounds, slump blocks, or channels and could seriously affect volcanic, tectonic, or sedimentological interpretations. Misinterpretation of these artifacts may result in positioning errors when seafloor bathymetry is used to navigate the ship. Considering these possible geological misinterpretations, a clear understanding of the Sea Beam system\u27s capabilities and limitations is deemed essential

Window Functions and Their Applications in Signal Processing

Window functions—otherwise known as weighting functions, tapering functions, or apodization functions—are mathematical functions that are zero-valued outside the chosen interval. They are well established as a vital part of digital signal processing. Window Functions and their Applications in Signal Processing presents an exhaustive and detailed account of window functions and their applications in signal processing, focusing on the areas of digital spectral analysis, design of FIR filters, pulse compression radar, and speech signal processing. Comprehensively reviewing previous research and recent developments, this book: Provides suggestions on how to choose a window function for particular applications Discusses Fourier analysis techniques and pitfalls in the computation of the DFT Introduces window functions in the continuous-time and discrete-time domains Considers two implementation strategies of window functions in the time- and frequency domain Explores well-known applications of window functions in the fields of radar, sonar, biomedical signal analysis, audio processing, and synthetic aperture rada

Window Functions and Their Applications in Signal Processing

Window functions—otherwise known as weighting functions, tapering functions, or apodization functions—are mathematical functions that are zero-valued outside the chosen interval. They are well established as a vital part of digital signal processing. Window Functions and their Applications in Signal Processing presents an exhaustive and detailed account of window functions and their applications in signal processing, focusing on the areas of digital spectral analysis, design of FIR filters, pulse compression radar, and speech signal processing. Comprehensively reviewing previous research and recent developments, this book: Provides suggestions on how to choose a window function for particular applications Discusses Fourier analysis techniques and pitfalls in the computation of the DFT Introduces window functions in the continuous-time and discrete-time domains Considers two implementation strategies of window functions in the time- and frequency domain Explores well-known applications of window functions in the fields of radar, sonar, biomedical signal analysis, audio processing, and synthetic aperture rada