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This paper discusses the problem of design of a pair of matched pulse shaping linear-phase FIR filters. The design involves obtaining a predetermined attenuation of the magnitude response in the stopband and a minimum level of ISI. The known design method based on the weighted Chebyshev approximation using the Remez algorithm with additional control of the transition band at one point and weight selection for the magnitude response level in the stopband is compared with several alternative approaches namely the SRRC function, nonlinear programming, convex optimization and semi-analytical procedure. Examples of pulse-shaping filters taken from the literature show that this method does not always result in repetition or improvement of known solutions. However, the modification proposed in the paper, related to the addition of several more conditions for the control of the transition band, can contribute to a significant improvement in these solutions both for stopband attenuation at the same ISI value and for each of these parameters. 2. Farhang-Boroujeny B. A square-root Nyquist (M) filter design for digital communication systems// IEEE Trans on SP, 2008, vol. 56, no. 5, pp. 2127-2132. 3. Ashrafi A. Optimized linear phase square-root Nyquist FIR filters for CDMA IS-95 and UMTS standards// Signal Processing, 2013, vol. 93, no. 4, pp. 866-873. 4. Traverso S. A family of square-root Nyquist filter with low group delay and high stopband attenuation// IEEE Commun. Letters, 2016, vol. 20, no. 6, pp. 1136-1139. 5. Xiao R., Lei Q., Guo X., Du W., Zhao Y. A design of two sub-stage square-root Nyquist matched filter// IEEE Access, 2018, vol. 6, may, pp. 23292-23302. 6. Mingazin A. T. Design quantized pulse-shaping FIR filters for digital communication system// Digital Signal processing. Russian Scientific and Technical Journal, 2021, no. 4, pp. 3-15. 7. Proposed EIA/TIA interim standard. Wideband spread spectrum digital cellular system dual-mode mobile station-base station compatibility standard. Tech. Rep. TR 45.5. Qualcomm Inc. San Diego. CA (Apr. 1992). 8. Universal mobile telecommunications systems (UMTS); UMTS terrestrial radio access (UTRA); concept evaluation. Tech. Rep. TR 101 146 version 3.0.0 (1997-12). Euro. Telecommun. Stand. Inst. Sophia Antipolis. France (Dec. 1997).
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The error in determining the location by the proposed algorithm compared with the existing hyperbolic method at 8178 points in the Asia-Pacific region. The data obtained made it possible to simulate and evaluate the working zones of two jointly used chains of pulse-phase radio navigation systems according to both algorithms. It shown that the use of the iterative position search method significantly expands the working area of chains when they used together. In addition, in most areas, the position determination error is significantly lower than in the hyperbolic method. A method introduced for quantitative assessment of the effectiveness of the iterative position search method in comparison with the hyperbolic method. Modeling the working area of several chains allows you to improve the efficiency of determining the deployment locations and formats of new systems. A quantitative analysis of the effectiveness of the proposed method allows us to conclude that when using the iterative position search algorithm, the size of the zone in which the position error is below 20 meters is approximately 11 times larger than the zone in which the hyperbolic method provides the same error. For an error below 40 meters, the size of the working area increases by a factor of 2.86. For an error below 60 meters, 2.7 times. The iterative position search algorithm is able to work with signals from two or more radio navigation circuits. The use of the results of the study will make it possible to determine the optimal deployment sites and formats for the operation of new combined radio navigation systems.
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Maslakov M.L., Ph.D., assistant professor, e-mail: maslakovml@gmail.com Saint-Petersburg State University of Aerospace Instrumentation Keywords:
At the same time, in non-stationary communication channels, as well as in case signal fading and/or hard signal-interference conditions, it is required to obtain appropriate estimates quickly enough, which significantly limits the possible size of the analyzed sample and the applicability of some known methods. The purpose of this work is to estimation of an empirical probability density function of the complex envelope coefficients of modulated signals received from a non-stationary channel with fading. To estimation an empirical two-dimensional probability density function of the complex envelope coefficients of modulated signals received from a channel with fading, the Parzen method or the method of kernel functions was used in the work. As shown in the work, the obtained empirical probability density function are smooth, independent of the probability of individual symbols, and also allow one to draw conclusions about the depth and nature of fading in the communication channel.
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Recognition of small UAVs is not an easy task due to the similarity of the radar characteristics of such targets and the parameters of their movement both among themselves. The recognition of targets can be carried out on the basis of the following features: the nature of the Doppler portrait of the reflected signal due to the peculiarities of the rotation of the propellers of a particular type of aircraft or the flapping of the wings of birds; radar image of the target formed by methods of inverse aperture synthesis; trajectory signs of the flight of the target, etc. The Bayesian classifier uses observable features as a basis and correlates objects to a certain class based on the maximum likelihood principle, which consists in assessing the degree of discrepancy between the statistical characteristics of the obtained samples of parameter values with their a priori values. Classifiers based on neural networks have high performance, however, the addition of a new class leads to the need to repeat the procedure of full network training on the entire existing set. The approach that allows combining the advantages of neutron and Bayesian methods can be based on the representation of the classification object as a system with a random jump-like structure. Evaluation of the parameters of such systems is carried out by Bayesian methods, and neural classifiers act as so-called indicators that ensure the formation of a final solution, taking into account their probabilistic characteristics for the correlation of an object to a given class. The neural network indicator is a deep learning neural network based on the SqueezeNet architecture and implemented using the Neural Networks Toolbox extension of the Matlab software package. As a training sample, the radar of the DJI Matrice S900 multicopter aircraft, the Orlan-10 and Bayraktar TB2 UAVs, as well as the Tomahawk BGM-109 cruise missile were used. The radar was formed in the CST Microwave Studio electrodynamic modeling environment using the inverse aperture synthesis method implemented in it. The training sample was a set of 700 radar images for each aircraft, obtained from various viewing angles. The images are formed for horizontal polarization of the electromagnetic wave using the monostatic radar method and the average wavelength of the probing signal is 5.5 cm. The width of the spectrum of the probing signal is 1 GHz, which provides a horizontal range resolution (x coordinate) of about 15 cm. The use of the proposed classifier in radar means will increase the efficiency of choosing a priority for counteraction, taking into account the degree of danger of targets and exclude secondary targets from processing to prevent overloading of radar and counteraction channels.
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It is shown that the shape and width of the amplitude-frequency characteristics of the synthesized filters remain constant when the filter tuning frequency is changed. The developed technique for the synthesis of tunable discrete band-pass and notch filters with a constant shape and width of the amplitude-frequency characteristic will be very useful in the construction of adaptive systems and signal processing devices, such as systems for detecting and filtering signals with an unknown frequency, Doppler velocity meters under varying Doppler frequency, systems for selecting moving targets in the presence of reflections from the earth's surface and moving hydrometeors. Keywords: discrete filters, frequency characteristics, z-transform, weight coefficients. 2. Popov D. I. Adaptive suppression of passive interference // Digital signal processing. 2014, No. 4. pp. 32-37. 3. Microprocessor automatic control systems. Under total ed. V.A. Besekersky. L.: Mechanical engineering. 1988. 355 p. 4. A. S. Kotousov and A. K. Morozov, Optimum Filtration and Noise Compensation. M.: Hotline-Telecom, 2008. 166 p. 5. Popov D. I. Adaptive detection of signals against the background of passive noise // Digital signal processing. 2014, No. 4. pp. 32-37. 6. S. I. Ziatdinov, Synthesis of Complex Discrete Filters, Izv. universities. Radioelectronics. 2017, No. 4. pp. 12-19. 7. Ziatdinov S. I. Synthesis of non-recursive discrete filters in the time domain // Information and control systems. 2016, No. 5. pp. 98-101. 8. Gold B., Reider N. Digital signal processing. M.: Soviet radio, 1973. 367 p. 9. Ziatdinov S. I. Analysis of linear systems based on transient characteristics / Information and control systems. 2016, No. 2. pp. 104-106. 10. S. I. Ziatdinov, Synthesis of Discrete Filters by Methods of Invariant Differential and Integral Equations, Izv. universities. Instrumentation. 2019. V. 62, No. 5. pp. 424-432. 11. Oppenheim A., Shafer R. Digital signal processing. M.: Technosfera, 2006. 855 p. 12. Kupriyanov M. S., Matyushkin B. D. Digital signal processing. St. Petersburg: Politekhnika, 2000. 592 p. 13. Besekersky V. A. Digital automatic systems. M.: Nauka, 1976. 575 p. 14. Gadzikovsky V. I. Theoretical foundations of digital signal processing. M.: Radio and communication, 2004. 344 p.
Based on the introduced criterion, a two-stage optimization problem has been solved. At the first stage, the optimal RF vector is determined, at the second stage - a multichannel filter (MF) of coherent accumulation. Optimization results are presented depending on the correlation properties of the interference and a comparison is made with the efficiency of optimal processing. The dependences of the optimal RF order on the magnitude of the dynamic range of interference in relation to the level of intrinsic noise are obtained. having a directly proportional character. The conditions are established under which a system of a fixed structure, the scheme of which is given, is achieved close to potential efficiency. The conditions for the use of tunable structure systems are considered, in which it is possible to approach the potential efficiency when changing the interference parameters in a relatively wide range only when optimizing the RF order by appropriate restructuring of the structure. A method for choosing the RF and MF orders is proposed, based on the relationship of the optimal RF order with the increment of the interference transmission coefficient at the RF output when its order changes. As a result of the analysis of the dependences of the increments of the passage coefficient, the condition for choosing the optimal order of the RF is established. A block diagram of the adaptive processing system of the transferred structure is given. 2. Richards M.A., Scheer J.A., Holm W.A. (Eds.). Principles of Modern Radar: Basic Principles. New York: SciTech Publishing, IET, Edison. 2010. 924 p. 3. Melvin W. L., Scheer J.A. (Eds.). Principles of Modern Radar: Advanced Techniques. New York: SciTech Publishing, IET, Edison, 2013. 846 p. 4. Radar Handbook / Ed. by M.I. Skolnik. 3rd ed. McGrawHill, 2008. 1352 p. 5. Popov D.I. Adaptacija nerekursivnyh rezhektornyh fil'trov // Izvestija vuzov. Ra-diojelektronika. 2009. vol. 52. no. 4. P. 46-55. (in Russian). 6. Popov D.I. Autocompensation of the Doppler phase of clutter // Cifrovaja obrabotka signalov. 2009. no 2. pp. 3033. (in Russian). 7. Popov D.I. Adaptive suppression of clutter // Cifrovaja obrabotka signalov. 2014. no. 4. pp. 32-37. (in Russian). 8. Popov D.I. Adaptivnije regektornjie filtrij kaskadnogo tipa // Cifrovaya obrabotka signalov. 2016. no. 2. pp. 53-56. (in Russian). 9. Popov D.I. Adaptive notch filter with real weights // Cifrovaya obrabotka signalov. 2017. no. 1. pp. 22-26. (in Russian). 10. Popov D.I. Optimizacja nerekursivnjih regektornjie filtrov s chastichnoj adaptaciej // Cifrovaya obrabotka signalov. 2018. no. 1. pp. 28-32. (in Russian). 11. Popov D.I. Optimizacija rezhektornyh fil'trov po verojatnostnomu kriteriju // Cifrovaja obrabotka signalov. 2021. no. 1. P. 55-58. (in Russian). 12. Popov D.I. Ocenivanie korreljacionnyh parametrov passivnyh pomeh // Radiopromyshlennost'. 2017. no 1. P. 57-62. (in Russian).
The AMR-WB speech codec is based on the algebraic code excited linear prediction technology (ACELP). Two frequency bands, 50 6400 Hz and 6400 7000 Hz, are coded separately. The input signal of the lower frequency band is pre-processed using a high-pass filter and a pre-emphasis filter. Linear Prediction (LP) analysis is performed on each frame. The set of LP parameters is converted to immittance spectrum pairs and vector quantized using split-multistage vector quantization. The speech frame is divided into four subframes of 5 ms each. The adaptive and fixed codebook parameters and pitch lag are transmitted every subframe. The bit allocation of the codec at different bit rates is shown. The higher frequency band is reconstructed in the decoder using the parameters of the
lower band and a random excitation. No information about the higher band is transmitted, except
in the 23,85 kb/s mode, where the higher band gain is transmitted. In other modes, the gain of the
higher band is adjusted relative to the lower band using voicing information. The spectrum of the
higher band is reconstructed by using a wideband LP filter generated from the lower band LP
filter. 2. Flanagan D.L. Analiz, sintez i vosprijatie rechi (Analysis, synthesis and perception of speech). Μ.: Svjaz' 1968. 396 p. 3. GOST R 50840-95. Peredacha rechi po traktam svijazi. Metodi ocenki kachestva, razborchivosti i uznavaemosti (Speech transmission over varies communication channels. Techniques for measurements of speech quality, intelligibility and voice identification) 1995. M: Publishing house of standards, 1996. 230 p. 4. ITU-T Recommendation G.722.2. Wideband coding of speech at around 16 kbit/s using Adaptive Multi-Rate Wideband (AMR-WB). 2003. 5. 3GPP TS 26.445. Codec for Enhanced Voice Services; Detailed Algorithmic Description (Release 15). 2018. 6. J.-P. Adoul, P. Mabilleau, M. Delprat, and S. Morissette, "Fast CELP coding based on algebraic codes", in Acoustics, Speech, and Signal Processing, IEEE Int Conf (ICASSP'87), April 1987, pp. 1957-1960.
2. Stephan Ten Brink "Convergence of iterative decoding", ELECTRONICS LETTERS, vol. 35, no. 10, May 1999, pages 806 808. 3. G. Liva and M. Chiani, "Protograph ldpc codes design based on exit analysis," in Proc. IEEE Globecom, Washington, USA, Nov. 2007, pp. 3250-3254. 4. Richardson T. Error floor of LDPC codes // Proc. 41st Allerton Conf. Comm., Control, and Comput., Monticello, IL. - 2003. P. 14261435. 5. Vukobratovic D., Senk V. Generalized ACE constrained progressive edge-growth LDPC code design. IEEE Communications Letters, 12(1):3234, 2008. 6. Bocharova I E., Johannesson R., Kudryashov B. D. Combinatorial optimization for improving QC LDPC codes performance. In 2013 IEEE International Symposium on Information Theory Proceedings (ISIT), pages 26512655. IEEE, 2013. 7. T. CCSDS, Synchronization and channel coding. recommendation for space data systems standards (No. 2). CCSDS 131. 0-B-2, Washington DC:CCSDS. 8. "Digital Video Broadcasting (DVB): Second generation framing structure channel coding and modulation systems for Broadcasting Interactive Services News Gathering and other broadband satellite applications: European", 06 2006. 9. "ETSI Standard EN 302 307", Digital Video Broadcasting (DVB); Second Generation Framing Structure Channel Coding and Modulation Systems for Broadcasting Interactive Services News Gathering and Other Broadband Satellite Applications Version 1.3.1, Mar. 2013. 10. "GMR-101.202 (ETSI TS 101 37613)", "GEO-Mobile Radio Interface Specifications; Part 1: General Specifications; Sub-part 3: General System Description; GMR-1 01.202". 11. https://aff3ct.github.io 12. E. Cavus, C. Haymes and B. Daneshrad, "Low BER performance estimation of LDPC codes via application of importance sampling to trapping sets", IEEE Transactions on Communications, vol. 57, no. 7, pp. 1886-1888, 2009. |