Novel acousto-optic systems for spectrum analysis and phased array radar signal processing

This paper describes and compares two particle excitation methods, square and sine wave, used in conjunction with novel application of Phase Doppler Anemometry (PDA) to obtain particle size and charge simultaneously in real time. Different signal processing strategies for particle velocity and size estimation are investigated, including Quadrature Demodulation (QD), spectral analysis and correlation technique. The system performance has been tested using Monte Carlo simulations obtained from the synthesized Doppler burst signals. Finally a mathematical model has been developed in order to estimate the percentage of particles captured in the measurement volume and successfully analyzed by the signal processing system leading to the optimization of the system parameters. It can be concluded that the signal processing system working in the square-wave excitation field and based on the spectral analysis performs better both in terms of the measurement range and the SNR requirement.

NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract Session: 2711 Teaching Hardware Design of Fixed-Point Digital Signal Processing Systems David V. Anderson1 and Tyson S. Hall2 1 Georgia Institute of Technology, Atlanta, GA 30332–0250, dva@ece.gatech.edu 2 Southern Adventist University, Collegedale, TN 37315–0370, tyson@southern.edu Abstract Signal processing theory and practice are enabling and driving forces behind multimedia de- vices, communications systems, and even such diverse fields as automotive and medical sys- tems. Over 90% of the signal processing systems on the market used fixed-point arithmetic because of the cost, power, and area savings that fixed-point systems provide. However, most colleges and universities do not teach or teach only a very little fixed-point signal process- ing. This issue is being addressed slowly around the country but now a new challenge or opportunity presents itself. As reconfigurable logic technology matures, field-programmable gate arrays (FPGAs) are increasingly used for signal processing systems. They have the ad- vantage of tremendous throughput, great flexibility, and system integration. The challenge is that signal processing in FPGAs is a much less constrained problem than signal processing in special purpose microprocessors. The opportunity arises in that it is now possible to explore more options and, more especially, to take a more systems-level approach to signal processing systems. In short, designing a signal processing system using FPGAs provides opportunities to look at many system design issues and trade-offs in a classroom setting. We have developed a course to teach signal processing in FPGAs at Georgia Institute of Technology and in this paper we consider the challenges and methods of teaching fixed- point system design in this course. We discuss the topics chosen and how they differ from traditional microprocessor-based courses. We also discuss how systems engineering concepts are woven into the course. 1 Motivation This paper describes the early development of a system design curriculum that uses field programmable gate arrays (FPGAs) to implement digital signal processing (DSP) systems. The goals of this curriculum are several-fold, including: • to prepare students for system design problems with which they are likely to be pre- sented upon graduation; Proceedings of the 2007 American Society for Engineering Education Annual Conference & Exposition Copyright c 2007, American Society for Engineering Education

It has been shown both theoretically [1] and experimentally [2] that a spectrum analyzer based on an externally driven spin torque nano-oscillator (STNOs) can perform high-speed, wide-band spectrum analysis in a microwave frequency band. In such a spectrum analyzer, an STNO generates a signal whose frequency is tuned in a linear manner over a scanning bandwidth Δf. Theoretical estimations show that when employing an STNO in spectrum analysis, the following can be achieved: a Δf of 10 GHz, a linear scanning rate ρ=Δf/T (where T is the scanning period) of up to 2 GHz/ns, all in a frequency range of operation between 200 MHz and 70 GHz [3]. The fast speed of frequency analysis in a STNO-based spectrum analyzer can be achieved mainly due to the nano-scale size of the STNO, and the consequent ns characteristic scanning times. At a sufficiently large scanning rate ρ, the accuracy of the frequency determination ΔF (defined as the minimum separation required to distinguish two neighboring frequencies) of an STNO-based spectrum analyzer is fundamentally limited by the bandwidth theorem. In contrast, at low scanning rates, this accuracy is limited by the STNO generation linewidth [4], which is determined by the thermal (or random-walk) noise that is causing the jitter of the STNO generation frequency. Fig. 1 shows the frequency accuracy ΔF as a function of the scanning rate ρ for the STNO-based spectrum analyzer [2], where the gray solid line is the result of numerical modeling, dash-dotted line is a result of the experimental measurement [2], and dashed line shows the limit due to the “bandwidth” theorem. It is evident that at sufficiently large scanning rate, ΔF approaches the fundamental limit ΔF =1/T, whereas at smaller ρ the ΔF is limited by the magnitude of the STNO linewidth.

In order to improve the efficiency for phased array radar's ESM, an ACO and SVM conjoint method is used in this paper to solve the problem of phased array radar signal recognition. By introducing ACO to supervise SVM parametric selection, the method is able to quickly discover seemly parameter value and improve SVM separation efficiency. Experimental results show that textual algorithm possess upper exactness rate to phased array radar that the whole pulse signals sorting can be identified. With normal-SVM and RST-SVM means to compare, the algorithm SVM parameter access time is short, thereby shorten the monolithic hour.

Joint tracking sequence and dwell time allocation for multi-target tracking with phased array radar

This paper describes a system for digital signal processing to control vibrating gyroscopes which will allow more flexibility and increase performance through a reduction in electronics noise. A close-loop control method based on quadrature demodulation (QD) is presented. Improvements in signal demodulation, noise suppression, phase shift and direct digital frequency synthesizer (DDS) are also proposed. The whole open-loop system is implemented on a FPGA (field programmable gate array) platform and tested. The resulting scale factor and nonlinearity are 7.1 mV/°/s and 0.55% respectively with the full scale of 400°/s.

In phased array antennas, the high side-lobe levels due to the amplitude quantization often need to be reduced to meet some requirements. In order to develop the digitalization of antenna arrays in phased array radars, the amplitude quantization of aperture distribution in array antennas is studied. In this paper, the random technique and a novel appropriate random technique are presented and used to reduce the side-lobe levels, and the side-lobe levels in the amplitude quantized array pattern are calculated. The reduction of side-lobe level due to amplitude quantization are introduced using the improving method and confirmed with computations, where the related parameters are modified and numerous patterns are computed and compared. The quasi-optimum patterns are also obtained and given.

Most existing radio frequency (RF) spectrum analyzers use conventional superheterodyne architecture to remove images associated with the down conversion of RF input frequency to some intermediate frequency (IF) for further processing, and their complexity increases as the frequency range of interest is extended. This article describes a novel digital system architecture for spectrum analyzers based on quadrature down conversion. Quadrature down conversion architectures where image responses are inherently rejected are normally used to analyze a single frequency or a very narrow frequency spectrum. This article proposes using quadrature architecture in an ultrawideband spectrum analysis application. A wideband spectrum analyzer receiver with compensation for gain and phase imbalances in the RF input range, as well as compensation for gain and phase imbalances within the IF passband complete with resolution bandwidth (RBW) filtering, video bandwidth (VBW) filtering, and amplitude detection, is implemented in a low-cost field-programmable gate arrays (FPGAs). The proposed method still achieves the desired image rejection performance specification, is power-efficient, and significantly simplifies the RF front-end hardware in comparison to state-of-the-art methods.

The biological inner ear, or cochlea, is a sophisticated signal processing system that performs spectrum analysis over an ultra-broadband frequency range of ~20 Hz to 20 kHz with exquisite sensitivity and high energy efficiency. Electronic cochlear models, which mimic the exponentially-tapered structure of the biological inner ear using transmission lines or filter cascades, have been shown to be fast and extremely efficient spectrum analyzers at both audio and radio frequencies. We have previously used this model to create single-chip RF spectrum analyzers, and have recently developed improved output encoding methods for such cochlea-like analyzers. A prototype analyzer has been designed in the UMC 65 nm RF-CMOS process. It includes a bidirectional cochlea model with 50 parallel exponentially-spaced output stages and analyzes the radio spectrum from 0.8-8.3 GHz. The outputs are encoded as delta-sigma (ΔΣ) modulated digital signals that are demodulated and analyzed in real-time by a digital back-end implemented on a field-programmable gate array (FPGA). The resulting system is expected to be useful as a broadband spectrum sensor in cognitive radio networks.

As active electronically steerable arrays become more prominent, a new paradigm of assigning bits to a set of digital phase shifters, necessary for analog and digital beamforming, is proposed. It is well known that a modern day digital phase shifter which is associated with each transmit/receive module typically relies on three to seven bits. Each of these phase shifters provide a desired resolution of 45° to 2.8125°, respectively. When an array is steered with a fixed precision set of phase shifters, there are some angles where results are significantly better than others. For example, six bit phase shifters can provide exact 11.25° differential phases in a linear array, but not 15°, and subsequent quantization errors lead to reduced pointing accuracy and increased sidelobe levels. However, these errors can be minimized if the set of shifters operate collectively instead of independently with “blind” quantization. In particular this study seeks the solution for the following problem: for a set of N phase shifters, each defined by B bits, determine the optimal way to distribute the N×B bits so that the array performance is maximized.

The design of a microstrip series-fed linear traveling-wave array is described in this paper. The array is composed of two symmetric subarrays formed by cascading an equal number of four-port aperture-coupled cross-patch elements and terminated on a two-port radiating matched load. Dual-linear and circular polarization can be achieved by appropriately exciting the array and by virtue of the symmetric arrangement of the antenna high polarization purity is obtained. A proof-of-concept linear array is developed and the corresponding numerical results performed through a full-wave approach based on the method of moments are presented.

Factors affecting the continuous wave Doppler spectrum for the diagnosis of carotid arterial disease

The Spectrum Sliding Analysis (SSA) is a dynamic spectrum analysis in which the next analysis interval differs from the previous one by including the next signal sample and excluding the first one from the previous analysis interval. Such a spectrum analysis is necessary for time-frequency localization of analyzed signals with given peculiarities. Using the well-known Fast Fourier Transform (FFT) towards this aim is not effective. Recursive algorithms which use only one complex multiplication for computing one spectrum sample during each analysis interval are more effective. The author improved one algorithm so that it is possible to use only one complex multiplication for computing two, four, and even eight (for complex signals) spectrum samples simultaneously. Problems of realization and application of the spectrum sliding analysis are also considered in the chapter. keywords: spectrum sliding analysis, dynamic spectrum analysis, recursive algorithms, sliding spectrum algorithms & analyzers, instant spectrum algorithms & analyzers, algorithms for instantaneous spectrum digital analyzers, multichannel filter

The phased array antenna can instantaneously direct a radar beam into a desired direction without mechanically moving the antenna. Anticipating an application to a phased array radar, adaptive control of the sampling interval for the tracking object is considered. Reducing the sampling interval for a target with high maneuverability prevents degradation of the tracking accuracy. For a target in straight‐line motion, the sampling interval is increased so that the number of observations is reduced for an efficient operation of radar resources. In this paper, the M3(Multiple Maneuver Model) filter is used as one of the tracking algorithms based on the multiple motion model, and a control scheme is proposed with a sampling interval based on the tracking error covariance matrix. By means of simulation, the tracking performance is compared with the case where the sampling interval is fixed. As a result, the tracking accuracy is improved by 15% during a maneuvering motion without increasing radar resources. © 2002 Wiley Periodicals, Inc. Electron Comm Jpn Pt 1, 85(10): 44–54, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecja.1130

Space-time adaptive processing (STAP) holds tremendous potential for the new generation airborne surveillance radar, in which the phased array antennas and pulse Doppler processing mode are adopted. A new STAP approach using the multiple-beam and multiple Doppler channels is presented here for airborne phased array radar. The approach with space-time multiple-beam (STMB) architecture is robust to array errors and has very low system degrees of freedom (DOFs). Hence, it has low sample support requirement and it is very suitable for the practical planar phased array radar under nonhomogeneous clutter environments. Meanwhile, a new nonhomogeneous detector (NHD) based on the correlation dimension (CD) is also proposed here, which is used as an effective method to screen tracing data prior to detection processing. It can further improve the performance of the STAP approach in the severely nonhomogeneous clutter environments. Therefore, a scheme that incorporates the correlation dimension nonhomogeneity detector (CD-NHD) with the STMB is recommended, which we term CD-NHD-STMB. The experimental simulation results indicate that: 1) the STMB processor is robust to array element error and has high performance under nonhomogeneous clutter environments; 2) the CD-NHD is also effective on the nonhomogeneous clutter. As a result, the CD-NHD-STMB scheme is robust to array element error and nonhomogeneous clutter, and therefore available for airborne phased array radar applications.