Digital Signal Processing |
Russian |
The algorithm for on-board compression of spaceborne SAR raw data Abstract According to the results of experimental studies, the proposed quantizer for a fixed average code length provides the least loss in the radar image (the highest quantization signal-to-noise ratio). Compared to the Lloyd-Max quantizer, the gain in signal-to-noise ratio for a fixed average code length is from 0.5 to 0.9 dB, and compared to a uniform quantizer, from 0.1 to 0.3 dB. Thus, experimental studies have shown that due to the deviation of the real distribution law of the values of the components of the complex signal of the radio hologram block from the ideal case, the real gain from the use of the proposed quantizer is about 2 times lower than theoretically predicted. Nevertheless, its use allows reducing the loss for a fixed compression ratio by approximately 1–3% compared to the uniform quantizer used in the FDBAQ algorithm. 2. Ushenkin V.A. Matematicheskaya model’ sinteza radiolokacionnyh izobrazheniy decimetrovogo razresheniya iz radiogologramm ot kosmicheskih RSA (Decimeter-resolution spaceborne SAR raw data focusing model) // Digital signal processing, 2018, no. 3, pp. 21–25. 3. Benz U., Strodl K., Moreira A. A Comparison of Several Algorithms for SAR Raw Data Compression // IEEE Trans. on Geoscience and Remote Sensing, 1995, vol. 33, no. 5, pp. 1266–1276. 4. Kuduvalli G., Dutkiewicz M., Cumming I. Synthetic Aperture Radar Signal Data Compression Using Block Adaptive Quantization // 1994 Science Information Management and Data Compression Workshop, 1994, pp. 43–57. 5. Attema E., Cafforio C., Gottwald M. et al. Flexible Dynamic Block Adaptive Quantization for Sentinel-1 SAR Missions // IEEE Geoscience and Remote Sensing Letters, 2010, vol. 7, no. 4, pp. 766–770.
Keywords: polarimetric decomposition, SAR image processing, high-altitude vegetation detection. Polarimetric decompositions of Pauli, Krogager, van Zijl, Freeman-Durden, Huygen, Barnes-Holm in two versions, the dominant scattering mechanism according to Claude-Potier and H-A-Alpha are considered. The analysis of the obtained results is carried out. The probabilities of correct and incorrect detection of forest cover are calculated. The results of the analysis showed that the Freeman-Durden and H-A-Alpha decompositions are the most applicable for the problem of monitoring the forest cover of the earth's surface. The research shows a high probability of forest cover detecting. In the future, it is expedient to conduct research on the involvement of additional features in order to reduce the probability of false detection of forest cover according to the data of polarimetric decompositions of radar images. References 2. Sovremennye technologii obrabotki dannykh distancionnogo zondirovaniya Zemli (Modern technologies for processing Earth remote sensing data) / Edited by V.V. Eremeev. – Moscow: FIZMATLIT, 2019. 3. Holm, W. A., Barnes R.M. On radar polarization mixed target state decomposition techniques // Proceedings 1988 USA National Radar Conference, 1988. P. 249-254. 4. Van Zyl, J. J. Application of Cloude’s target decomposition theorem to polarimetric imaging radar data // Proceedings SPIE conference of radar polarimetry, 1992. Vol 1748. P. 184-212. 5. Freeman A., Durden S.L. A three-component scattering model for polarimetric SAR data // IEEE Trans. on Geoscience and Remote Sensing, 1998. Vol. 36 (3). P. 936-973 6. Krogager E. A new decomposition of the radar target scattering matrix // Electronics Letter. 1990. Vol. 26 (18). P. 1525–1526. 7. Solovyev A.V., Ushenkin V.A. Analiz prigodnosti polarimetricheskih dekompozicviy kosmicheskih radiolokacionnyh izobrazheniy dlya obnaruzheniya visotnoy rastitel’nosti (Analysis of the suitability of polarimetric decomposition of space radar images for the detection of high-attitude vegetation) // Proceeding of the IV International Scientific and Technical Forum: in 10 volumes. Vol. 6. – Ryazan: Book Jet, 2021. – P. 5-10. Influence of hindrances on algorithms processings of the signal of differential frequency short-range frequency range finder
Abstract The algorithm 1 consists in accumulation during an interval of frequency modulation of the counting of weight function calculated in points of provision of zero SDF (points in which SDF crosses zero level). After the end of accumulation calculation of the measured distance by multiplication of the saved-up sum by the size of a discrete error of frequency range finder is made. Weight function is the middle of an interval of frequency modulation symmetric relatively with a maximum in the center and smooth falling off to zero in extreme points of this interval. The algorithm 2 is intended for the accounting of nonlinearity of the modulation characteristic of the transmitter and based on polynomial approximation of dependence on time of frequency of the radiated signal. Such approximation allows to work out necessary quantity of the linear equations of rather unknown coefficients of the approximating expression, the radiated frequency corresponding to situation on an axis of time of the first zero SDF and size of reorganization of frequency of the radiated signal upon transition from one zero to next. Two additional equations are worked out by a task of two known frequencies in the range of modulation and definition of the moments of coincidence of the radiated frequency to one of set. On this system of the linear equations the size of reorganization of the radiated frequency is calculated upon transition from one zero to another, next. Knowledge of this shift allows to calculate the measured distance. Assessment of a methodical error in ideal conditions is executed. For the first algorithm this size is given in literature. For the second algorithm assessment is executed about the help of numerical calculation of the measured distance with the given formulas. At both algorithms the methodical error is negligible. Existence of a hindrance causes the shift of zero SDF from their exact value and respectively to an additional error of measurement of distance. At rather small size of a hindrance in relation to useful SDF it is possible to receive formulas for the size of shift of each zero SDF under the influence of a hindrance. These formulas allow to receive for the first algorithm analytical expression for an additional error. For the second algorithm the additional error was estimated by means of numerical calculations for the given formulas. It is as a result received that use of the first algorithm in the conditions of influence of a hindrance leads to emergence of virtual hindrances on local distances, smaller distances to the disturbing reflector. At the second algorithm in the presence of a hindrance uniform increase in level of an error at any distances is observed Algorithms were compared to the help of numerical modeling.
Practical recommendations about application of the specified algorithms are formulated.
2. Muhammed Abd-Vahab Ismail. Radiolokacionnii visotomer s dvoinoi chastotnoi modulaciei (The radar altimeter with double frequency modulation). - M.: Izd-vo inostrannoi literaturi, 1957. – 135 p. 3. Fundamentals of Short-Range FM Radar / I.V. Komarov, S.M. Smolskiy - Artech House Publishers; Norwood, MA. 2003. - 289 p. 4. Precision FMCW Short-Rang Radar for Industrial Applications / B.A. Atayants, V.M. Davydochkin, V.V. Ezerski, V.S. Parshin, S.M. Smolskiy - Artech House publishers; Norwood, MA. 2014. – 320 p. 5. Ezerski V.V. Metodicheskaja pogreshnost datchika rasstojania na baze chastotno-modulirovannogo dalnomera s vesovim sglagivaniem oshibki diskretnosti (Methodical error of the sensor of distance on the basis of a frequency-modulated range finder with weight smoothing of an error of discretization) // Izmeritelnaja tehnika. 2003. ¹ 9. P. 22-25. 6. Baranov I.V., Ezerski V.V. Optimizacia parametrov moduliacii v blignei chastotnoi radiolokacii pri vesovom usrednenii raznostnoi chastoti (Optimization of parameters of modulation in a near frequency radar-location at weight averaging of differential frequency) // Vestnik Pazanskogo gosudarstvennogo radiotehnicheskogo universiteta. 2009. ¹ 28. P. 30-37. 7. Atayants B.A., Ezerski V.V., Shahtarin B.I.,Smolskiy S.M. Problema shumov i nelineinost moduliacionnoi harakteristiki peredatchika v precizionnih promishlennih sistemah blignei chastotnoi radioloracii (Problem of noise and nonlinearity of the modulation characteristic of the transmitter in precision industrial systems of a near frequency radar-location) // Uspehi sovremennoi radioelektroniki, 2008, ¹ 3. P. 3-29. 8. Patent 2234108 Rosiiskoi Federacii, G01 S 13/34. Sposob izmerenia rasstojania (varianti ) (Way of measurement of distance (options) ) / B.A. Atayants, V.V. Ezerski, I.V. Baranov, V.A. Bolonin, V.M. Davidochkin, V.A. Pronin. 9. Baranov I.V., V.V. Ezerski. Vlijanie pomeh na pogreshnost izmerenia rasstoiania v chastotnom dalnomere promishlennogo primenenia (Influence of hindrances on an error of measurement of distance in a frequency range finder of industrial application) // Vestnik Pazanskogo gosudarstvennogo radiotehnicheskogo universiteta. 2011. ¹ 37. P. 34-40. 10. Otechestvennie radiolokacionnie i volnovodnie urovnemeri s chastotnoi moduliaciei. Promishlennoe primenenie. Monografia (Domestic radar and waveguide level gages with frequency modulation. Industrial application. Monograph) B.A. Atayants, L.S. Atayants, I.V. Baranov, M.B. Bronin, V.M. Davidochkin, U.V. Mazalov, S.V. Maiorov, D.J. Nagorni, V.S. Parshin, V.A. Pronin, Pod. Red. B.A. Atayants - Ryazan: GUP RO «Ryazanskaia oblastnaia tipografia» 2021. – 388 p.
Abstract Purpose: development and analysis of the realizable characteristics of multi-criteria synthesis of direct-sequence spread spectrum radio signals for communication systems adaptation to combination of additive "white" Gaussian noise (AWGN), structural and narrow-band interferences. Results: in comparison with the known signals, the synthesized ones increase interference immunity up to 9 dB (in term signal-to-interference ratio) under action of AWGN, structural and narrow-band interference while maintaining the noise immunity threshold at the level of QPSK signal at action of only AWGN. Practical relevance: the results obtained indicate the advisability of using a class of synthesized direct-sequence spread spectrum radio signals to ensure effective adaptation of communication systems (without changing the spectral range) to the action of AWGN, structural and narrow-band interferences. References 2. Blahut R. E. Theory and practice of error control codes. Addison-Wesley, 1983. 3. Widrow B., Stearns S. Adaptive signal processing. M.: Radio i sviaz`, 1989. 440 p. (In Russ.). 4. Mitola J. Cognitive radio for flexible mobile communications // Mobile Multimedia Communications, 1999. (MoMuC '99) 1999 IEEE International Workshop. – 1999. – P. 3–10. 5. Hu F., Chen B., Zhu K. Full spectrum sharing in cognitive radio networks toward 5G: A survey //IEEE Access. 2018. vol. 6. pp. 15754-15776. 6. Lisnichuk A.A., “Multi-criteria synthesis procedure of DSSS signals for cognitive ra-dio systems adaptation to complex interference environment,” Vestnik RGRTU, No. 66-1, 2018, pp. 9-15. (In Russ.). DOI: 10.21667/1995-4565-2018-66-4-1-9-15 7. Lisnichuk A.A., Kirillov S.N., “Analysis of cognitive radio systems characteristics adapting to narrow-band interference effect based on synthesized four-position radio signals,” Vestnik RGRTU, No. 66-1, 2018, pp. 3-8. (In Russ.). DOI: 10.21667/1995-4565-2018-66-4-1-3-8 8. Kirillov S.N., Lisnichuk A.A., “The multi-criteria synthesis of signal-code sequence based on dependent signals to adapt data communication radio system to narrow-band interfer-ence,” Vestnik RGRTU, No. 4, 2017, pp. 3-12. (In Russ.). 9. Kirillov S. N., Pokrovskij P. S., Lisnichuk A. A., “The multi-criteria synthesis of four-position radio signal by code sequence ensemble for adapt data communication radio system to structural interference,” Radiotehnika. 2016. no 8. pp. 117-124. (In Russian). 10. Gutkin L.S., Optimizacija radiojelektronnyh ustrojstv [Optimization of radio-electronic devices] M.: Sov. radio. 1975. 368 p. (In Russ.). 11. S. N. Kirillov, A. A. Lisnichuk, “Multi-criteria signal synthesis procedure for adapt-ing cognitive radio systems to the influence of interfering factors in the Arctic,” IOP Conf. Series: Earth and Environmental Science. Vol. 302, No. 1, p. 012059. DOI: 10.1088/1755-1315/302/1/012059
Abstract References 2. Kaushal H. Underwater optical wireless communication [Tekst] / H. Kaushal, G. Kaddoum // IEEE Access. Vol. 4, 2016. P. 1518-1547. 3. Bloom S. Understanding the performance of free-space optics [Tekst] / S. Bloom, E. Korevaar, J. Schuster, H. Willebrand // Journal of optical networking. Vol.2/ No. 6, 2003, pp. 178-200. 4. Kirillov S.N. Propusknaya sposobnost' podvodnogo opticheskogo kanala peredachi infor-macii s kodoimpul'snoj modulyaciej po intensivnosti [Tekst] / S. N. Kirillov, L. V. Aronov // Vestnik RGRTU. 2020. ¹ 4 (74). S. 3-13. DOI: 10.21667/1995-4565-2020-74-3-13k. 5. Pratt V.K. Lazernye sistemy svyazi / per. s angl. pod red. A.G. SHeremet'eva. [Tekst]. M.: Radio i svyaz'., 1993. 232 s. 6. Baskakov S.I. Radiotekhnicheskie cepi i signaly. 3-e izd. [Tekst] // S.I. Baskakov. /M.: Vysshaya shkola, 2000. 462s. 7. Kuznecov S. Sistema opticheskoj svyazi v podvodnoj srede [Tekst] / S. Kuznecov, B. Ognev, S. Polyakov // Pervaya milya . 2014. ¹ 2. S. 46-51. 8. Abd El–Naser A. Mohamed Underwater wireless optical communications for short range typical ocean water types [Tekst] / Abd El–Naser A. Mohamed, Hamdy A. Sharshar, Ahmed Nabih Zaki Rashed, Enab Salah El-dien // Canadian journal on electrical and electronics engineering. 2012. No. 7. Vol. 3. P. 344-361. 9. Zolotarev V. V. Pomekhoustojchivoe kodirovanie. Metody i algoritmy: spravochnik / pod red. chl.-kor. RAN YU. B. Zubareva / V. V. Zolotarev, G. V. Ovechkin. M. : Goryachaya liniya-Telekom, 2004. 126 s. 10. Kirillov S.N. Algoritm ob"ektivnoj ocenki kachestva dekodirovannogo rechevogo signa-la na osnove izmeneniya spektral'noj dinamiki kriticheskih polos spektra / S.N. Kirillov, V.T. Dmitriev, YA.O. Kartavenko // Vestnik RGRTU, 2011. ¹3(37). S.3-7. 11. Kirillov S.N. Kompleksnyj algoritm ob"ektivnoj ocenki kachestva dekodirovannogo rechevogo signala pri dejstvii akusticheskih pomekh / S.N. Kirillov, V.T. Dmitriev // Trudy SPIIRAN 2018 ¹1. S. 34 -55.
Algebraic approach to the direction finding of objects in a multi-position re-ceiver system Abstract The purpose of the work. To improve the efficiency of multi-position location systems for potentially hazardous objects for recreation areas and private areas by developing and researching a common approach applicable to multiple spectral bands in systems of different physical uses. Results. The paper formulates a general algebraic approach to solving the problem of direction finding of objects in a multi-position receiver system. In receivers, angular coordinates of sources of reflection or radiation signals are measured, which are converted into coordinates of direction vectors orts to sources. Orts are distributed to objects by means of criterion of sufficient condition of vectors conjugation. Detection of objects is carried out on the basis of a statistical criterion. Estimates of objects position coordinates and velocity vectors are found from the solution of systems of linear equations in accordance with methods of estimation theory. Analysis of covariance evaluation matrices provides a recommendation for the spatial location of receivers, providing minimal estimation errors. Based on the general criterion of vectors conjugation, a more accurate mutual orientation of receiver coordinate systems is carried out. The work summarizes the previously obtained results and complements them with the results of experimental studies by computer modeling method. The results of the simulation compared to alternative approaches are presented. There is a plan to continue the work. Practical significance. The results of the work can be used in radio engineering, hydro-acoustic, radiometric and optical objects tracking systems at short range. It is possible to use ultrasonic location in medical diagnostic systems and robot-technical systems. References 2. Chernyak V.S. Multi-position radar. M.: Radio and communications, 1993. 416 p. (in Russian) 3. Lipsky Stephen E. Microwave passive direction finding. Raleigh, USA: SciTech Publishing, Inc., 2004. 320 p. (in English) 4. P. Nomikos, D. Economou, G. Limnaios and K.C. Zikidis, Presentation and feasibility study of passive radars // Air Force Rev Mag (in Greek), 107, (2016). P. 86–103. (in English) 5. Klochko V.K., Gudkov S. M., Nguyen C.H. Estimation of objects spatial coordinates in thermal and radio vision systems // Bulletin of Ryazan State Radio and Technical University. 2018. ¹ 1. P. 27 - 33, DOI: 10.21667/1995-4565-2018-63-1-27-33. (in Russian) 6. Klochko V.K., Gudkov S. M., Nguyen C. H. Comparative analysis of methods for estimatingthe coordinates of objects in a passive radio vision system // Bulletin of the Ryazan Public Radio Engineering University. 2018. ¹ 2. S. 23 - 28, DOI: 10.21667/1995-4565-2018-64-2-23-28. (in Russian) 7. Klochko V.K., Gudkov S. M., Nguyen C. H. Analysis of errors in the transfer of coordinates of objects in the system of combined receivers // Bulletin of Ryazan State Radio Engineering University. 2019. ¹ 69. S. 33 - 41, DOI: 10.21667/1995-4565-2019-69-33-41. (in Russian) 8. Klochko V.K. Direction finding of moving objects of the multi-position Doppler system theme // Radio engineering. 2020. T. 84, NO. 11 (21). P. 5 - 12, DOI: 10.18127/j00338486-202011(21)-01. (in Russian) 9. Ohrimenko A.G. Varianty resheniya zadachi otozhdestvleniya pelengov v passivnyh mno-gopozicionnyh uglomernyh sistemah // Izvestiya vuzov. Radioelektronika. 2002. T. 45, ¹ 6. S. 12 – 19.
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The cumbersomeness of the corresponding algorithms is the reason for the need to simplify them, which leads either to adaptive notch filters with time-variable real weight coefficients, or to notch filters with partial adaptation (autocompensation of the Doppler phase of interference) and a time-variable weight vector optimized in a priori known range of changes in the width of the interference spectrum. As a result of statistical averaging of the transfer functions, the results for the speed characteristics of these filters are obtained, depending on the volume of the training sample and the parameters of the time structure of the processed samples. The analysis of the speed characteristics of the filters was carried out separately for the cutting zone and the transparency zone, depending on the volume of the training sample, without imposing restrictions on the filter parameters, spectral-correlation properties of interference and parameters of the time structure of the processed samples. The analysis allows us to conclude that the use of filters during wobbling, which ensure the adaptation of the rejection zone to the spectral-correlation properties of the interference, leads to the elimination of the contradiction between the tasks of ensuring the linearity of the speed characteristics in the transparency zone and achieving high efficiency of passive interference suppression. 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. McGraw–Hill, 2008. 1352 p. 5. Popov D.I. Adaptacija nerekursivnyh rezhektornyh fil'trov // Izvestija vuzov. Radiojelektronika. 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. 30–33. (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. Rezhektirovanie passivnyh pomeh pri vobuljacii perioda povtorenija // Radiotehnika. 2015. no. 5. P. 97-101. (in Russian). 13. Popov D.I. Analiz algoritmov adaptivnogo rezhektirovanija passivnyh pomeh // Radiotehnika. 2016. no. 8. P. 148-152. (in Russian). 14. Popov D.I. Analiz rezhektornyh fil'trov s dejstvitel'nymi vesovymi kojefficientami // Radiotehnika. 2018. no. 5. P. 49-54. (in Russian)
Improving the accuracy of determining the coordinates of radio emission sources using space-based direction finders 2. Belov V.I. The Theory of Phase Measurement Systems. Tomsk, State University of Management Systems and Radio Electronics, 2007. 147 p. (in Russ.). 3. Lyons R.G. Understanding Digital Signal Processing. 2nd ed. Prentice Hall PTR, 2004. 688 p. (Russ. ed.: Laions R. Tsifrovaia obrabotka signalov. Moscow, Binom-Press, 2006. 656 p.).
Testing of the channel matrix in the time-sharing mode is accompanied by significant errors and an increase in the probability of outage, especially when the number of receiving and transmitting antennas is great. It was found that the accuracy of testing of the channel coefficients matrix is significantly affected by the long-term correlation of the phase noise of the transmitter, determined by the Hurst index. Therefore, when designing a MIMO system, it is necessary to use oscillators with a low level of phase noise in the low frequency region, as well as to use PLL systems with highly stable reference oscillators. 2. D. S. Baum, H. Bolcskei, “Information-Theoretic Analysis of MIMO Channel Sounding,” IEEE Transactions on Information Theory, 2011, vol. 57, no. 11, pp. 7555-7577. 3. D.S. Baum, H. Bolcskei, “Impact of Phase Noise on MIMO Channel Measurement Accuracy,” IEEE 60th Vehicular Technology Conference, 2004, DOI: 10.1109/VETECF. 2004.1400307, pp.34-38. 4. V.T. Ermolayev, A.G. Flaksman, I.P. Kovalyov, Averin I.M., “Weight Error Loss in MIMO Systems Using Eigenchannel Technique”, Proceedings of the 1st International Conference on Antenna Theory and Techniques (ICATT'03). Sevastopol, Ukraine, 2003, pp. 333-336. 5. Cronover R M Introduction to Fractals and Chaos. Jones and Bartlett Publishers, 1995. 6. Bochkov G.N., Kuzovlev Yu. Ye. Novoye v issledovanijah 1/f shuma (New in the 1/f noise investigation) // Uspehi phisicheskih nauk, 1983, vol. 1, no 141, pp. 151-176. 7. Thomas H. Lee, Design of CMOS Radio-Frequency Integrated Circuits, Cambridge University Press, 2004. 8. B. Kaukalys, M. Alaburda, J. Ruseckas, “Modeling non-Gaussian 1/f Noise by the Stochastic Differential Equations,” Noise and Fluctuations: 19th International Conference on Noise and Fluctuations - ICNF 2007, AIP Conference Proceeding, 2007, vol. 922, pp. 439-442. 9. Yu. V. Mamontov, M. Willander, “Long Asymptotic Correlation Time for non-Linear Autonomous Ito’s Stochastic Differential Equation,” Nonlinear Dynamics 12: 1997. Kluwer Academic Publishers, pp.399-411. 10. V. Kuhn, Wireless Communications over MIMO Channels: Applications to CDMA and Multiple Antenna Systems, John Wiley & Sons, 2006. 11. L.J. Greenstein, S. Ghassemzadeh, V.Erceg, D.G. Michelson, “Ricean K-factors in Narrowband Fixed Wireless Channels: Theory, Experiments, and Statistical Models,” IEEE Transactions on Vehicular Technology, 2009, vol. 58, no. 8, pp. 4000–4012. 12. J. Beran, Statistics for Long-Memory Processes, New York: Chapman and Hall, 1994. 315 p. 13. Belchikov S. Fazovyj shum: kak spustit'sya nizhe -120 dBn/Gc na otstrojke 10 kGc v diapazone chastot do 14 GGc ili bor'ba za decibely (Phase noise: how to go below -120 dBñ/Hz at 10 kHz tuning in the frequency range up to 14 GHz or struggle for decibels) // Komponenty I tekhnologii, 2009, no.5, pp. 139-146.
To increase the speed of recognition in one radar sweep, it is proposed preliminarily to de-correlate the received signals at each of the carrier frequencies. The proposed method of increasing the speed of target recognition relates to the digital processing of radar signals. It is shown that the nature of fluctuations of reflected signals at different carrier frequencies can be used to recognize detected objects by their longitudinal size. In particular, this recognition is based on the relationship of the value of the normalized inter-frequency correlation coefficient with the linear dimensions of the object. The larger the object size, the smaller the inter-frequency correlation coefficient.
This method allows effective recognition of objects by an inter-frequency correlation coefficient for independent observations, which leads to the use of received signals from several radar sweeps and large time costs. If we use samples of observations in one sweep, forming an estimate of the inter-frequency coefficient we get a significant decrease in the probability of correct recognition of objects. In order to overcome this disadvantage and increase performance without reducing the efficiency of recognizing objects by their longitudinal size, a method of recognition in one sweep is proposed, in which, prior to forming an estimate of the inter-frequency correlation coefficient, decorrelation of observation samples is performed at each carrier frequency. Decorrelation of observation samples can be performed using a filter with a finite impulse response (FIR filter). 2. Bartenev V.G. Patent "Method of radar classification using of an inter-frequency correlation coefficient" No. 2769217, Published: 20.04.2021 3. Bartenev V.G. On some features of the formation of an inter-frequency correlation coefficient // Modern Electronics, 2021. No. 3, 4. Bartenev V.G. Quasi-optimal adaptive algorithms for signal detection // Modern Electronics, 2011. No.2, 5. Bartenev V.G. On the distribution of the evaluation of the correlation coefficient module// Modern Electronics, 2020. No.8, 6. Potemkin V.G. “Handbook of MATLAB” Data analysis and processing. http://matlab.exponenta.ru/ml/book2/chapter8/
Thresholding in multi-frame Detection of a Reflected Radar Signal the Background of Nonstationary Uncorrelated Noise In this article, an algorithm for calculating the detection threshold is developed, which is used for the multi-frame detection algorithm against the background of uncorrelated noise that is non-stationary in variance. An analytical expression is found for the probability distribution density of a random variable at the input of the multi-frame accumulation algorithm, which is the ratio of a random variable with an exponential distribution law and a random variable with a gamma distribution. It is shown that the distribution density of this random variable does not depend on the noise variance, but depends on the sample size used to estimate the variance. The effect of the sample size used to estimate the noise variance on the detection characteristics of the intersurvey accumulation of reflected signals is analyzed. It is shown by numerical simulation that with a sample size M greater than 64 samples, the loss in the threshold signal-to-noise ratio does not exceed 0.1 dB compared to the inter-survey accumulation algorithm, in which the value of the noise variance in each survey is known exactly. 2. Blackman S., Popoli R. Design and analysis of modern tracking systems. L. Artech House: 1999. 1185 p. 3. Johnston L. A., Krishnamurthy V. Performance analysis of a dynamic programming track before detect algorithm // IEEE Transactions Aerospace Electronics System. 2002. vol. 38. pp. 228-242. 4. Tonissen S.M., Evans R.J. Performance of dynamic programming techniques foe track-before-detect // IEEE Transactions Aerospace Electronics System. 1996. vol. 32. pp. 1440-1451. 5. Belokurov V.A. Stabilization of the false alarm level when an object is detected against the background of non-Gaussian noise // Vestnik of the Ryazan State Radio Engineering University. 2018 ¹. 4. pp. 22-27. 6. Shulin L., Xinliang C., Tao Z., Le Z. New analytical approach to detection threshold of a dynamic programming track-before-detect algorithm // Radar, sonar and navigation. 2013. ¹8. pp. 773-779. 7. Barniv Y. Dynamic programming solution for detecting dim moving target // IEEE Transactions Aerospace Electronics System. 1985. ¹ 1. pp. 144-156. 8. Goryainov V.T., Zhuravlev A.G., Tikhonov V.I. Statistical radio engineering: Examples and tasks. Textbook for universities / Ed. V.I. Tikhonov. M.: Sov. radio. 1980. 544 p. 9. Gradshteyn I.S., Ryzhik I.M. Table of integrals, series, and products. L. Elsevier: 2007. 1221 p. 10. Gumbel E.J. Statistics of Extremes. New York. 2004. 11. Kryanev A. V., Lukin G. V., Udumyan D. K. Metric analysis and data processing. M.: Fizmatlit, 2012. 308 p.
Multirate signal processing in systems data transmission The first cycle of work was aimed at building digital subsystems of signal analysis and synthesis in relation to telecommunications systems and was associated with the development of converters of the type of channel compaction – transmultiplexers. The subsequent development of the theory of multi-rate signal processing contributed to rapid progress in the development of new computationally efficient methods of analysis/synthesis signals using multi-stage pyramidal structures, a polyphase form of implementation and the FFT algorithm. Broadband communication systems with many carriers, as an alternative to the classic OFDM, have become a new stage in the development and application of methods and algorithms for signal analysis/synthesis. At the same time, in some areas, such as cognitive radio, wireless transmission systems with multi–user access on the "mobile subscriber - base station" line, OFDM technology is difficult to implement due to synchronization problems. In these and other applications, the use of FBMC technology (banks of filters with many carriers) provides the best solution in terms of spectral and energy efficiency. Since the transition from classical OFDM to FBMC technology leads to a significant increase in computational costs, all the attention of researchers and developers was connected with the search for new more computationally efficient FBMC methods and algorithms – the construction of banks of digital bandpass filters. Therefore, subsequent research was carried out in the field of combining OFDM and FBMC technology. 2. Zubarev YU.B., Vityazev V.V., Dvorkovich V.P. Cifrovaya obrabotka signalov – informatika real'nogo vremeni // Cifrovaya obrabotka signalov. 1999. ¹ 1. C. 5-17. 3. Crochiere R.E., Rabiner L. Multirate Digital Signal Processing. Prentice Hall. Englewood Cliffs. NJ, 1983. 4. Vityazev V.V. Cifrovaya chastotnaya selekciya signalov. M.: Radio i svyaz', 1993. 240 s. 5. Vaidyanathan P.P. Multirate Systems and Filter Banks. Prentice Hall. Englewood Cliffs. NJ, 1993. 6. Mitra S.K. Digital Signal Processing: a computer-based approach. McGraw-Hill. Comp. Inc., 1998. 7. Ajficher E.S., Dzhervis B.U. Cifrovaya obrabotka Cifrovaya Obrabotka Signalov ¹1/2022 67 signalov: prakticheskij kurs: Per. s angl. M.: Izd. dom «Vil'yams», 2004. 992 s. 8. The Digital Signal Processing Handbook / Ed. Vijay K. Madisetti, Douglas B. Williams by CRC Press LLC, 1998. 9. Vityazev V.V. Mnogoskorostnaya adaptivnaya obrabotka signalov // Radiotekhnika. 2012. ¹ 3. S. 17-29. 10. Vityazev V.V., Nikishkin P.B. Mnogoskorostnaya obrabotka signalov v sistemah telekommunikacij // Elektrosvyaz'. 2013. ¹ 11. S. 49-56. 11. SHojermann X., Gekler X. Sistematizirovannyj obzor cifrovyh metodov preobrazovaniya vida uplotneniya kanalov // TIIER. 1981. T. 69. ¹ 11. S. 52-84. 12. Farhang-Boroujeny B. Signal Processing Techniques for Software Radios// Lulu publishing house, 2010. 13. Behrouz Farhang-Boroujeny. OFDM Versus Filter Bank Multicarrier // IEEE Signal Processing Magazine, 2011, Vol. 28, ¹ 3, P. 92-112. 14. Lin L. and Farhang-Boroujeny B. Cosine modulated multitone modulation for very high-speed digital subscriber lines // EURASIP J. Appl. Signal Processing, -2006, Aprticle ID 19329. 15. Vityazev V.V., Ovinnikov A.A. Metody analiza/ sinteza signalov v sistemah besprovodnoj svyazi so mnogimi nesushchimi // Elektrosvyaz'. 2013. ¹ 9. S. 28-32. 16. Vityazev V.V., Nikishkin P.B. Metod analiza/sinteza signalov v sisteme peredachi dannyh s chastotnym uplotneniem kanalov // Elektrosvyaz', 2014. ¹ 12. S. 4-9. 17. Vityazev V.V., Vityazev S.V., Zajcev A.A. Mnogoskorostnaya obrabotka signalov: retrospektiva i sovremennoe sostoyanie, chast' 2 // Cifrovaya obrabotka signalov. 2008. ¹ 3. S. 2-9. 18. Vityazev V.V. Nikishkin P.B. Banki fil'trov i OFDM v sistemah shirokopolosnoj peredachi dannyh. // Cifrovaya obrabotka signalov. 2015 ¹ 4, S. 30-34. 19. Vityazev V.V., Goryushkin R.S. Analiz shumov kvantovaniya mnogoskorostnyh struktur uzkopolosnyh KIH filtrov // Cifrovaya obrabotka signalov. 2015. ¹ 4. S. 35-39. 20. Gel'gor A.L., Popov E.A. Sistema cifrovogo televizionnogo veshchaniya standarta DVB-T: Ucheb. posobie. SPb.: Izd-vo Politekhn. un-ta, 2010. 207 s. 21. Vityazev V.V., Nikishkin P.B.Issledovanie effektov Doplera na OFDM i SUB-OFDM signaly // 1-ya Vserossijskaya konferenciya «Sovremennye tekhnologii obrabotki signalov», Moskva, Rossiya, doklady konferencii, 2018. 22. Vityazev V.V., Nikishkin P.B. Sravnenie effektivnosti tekhnologij OFDM i SUB-OFSM pri razlichnyh meshayushchih vozdejstviyah v kanale svyazi. // 21-ya Mezhdunarodnaya konferenciya «Cifrovaya obrabotka signalov i ee primenenie – DSPA-2019», Moskva, Rossiya, doklady. 2019. Kniga 1. S. 6-10 23. Majkov D.YU., Vershinin A.S. Vliyanie effektov Doplera na OFDM signal. Molodoj uchenyj. 2014. ¹ 21. S. 175-179. URL https://moluch.ru/archive/80/14271/. 24. Bakulin M.G., Krejndelin V.B., Shloma A.M., Shumov A.P. Tekhnologiya OFDM: Uchebnoe posobie dlya vuzov / M.: Goryachaya liniya – Telekom, 2017. 352 s. ISBN 978-5- 9912-0549-8. 25. Vityazev V.V., Nikishkin P.B. Issledovanie tekhnologij OFDM i SUB-OFDM pri razlichnyh meshayushchih vozdejstviyah v kanale svyazi. // 22-ya Mezhdunarodnaya konferenciya «Cifrovaya obrabotka signalov i ee primenenie – DSPA-2020», Moskva, Rossiya, doklady. 2020. 26. JG Andrews, S Buzzi, W Choi, SV Hanly, A Lozano, ACK Soong, JC Zhang, What will 5G be? IEEE J. Sel. 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Evaluation of the efficiency of the 1967VN028 processor of JSC "ICC Milandr" in the processing of radar signals by the MOS module The main purpose of this work is to evaluate the operability and efficiency of the 1967VN028 processor and DSP modules based on it, as well as the possibility of replacing TigerSHARC processors from Analog Devices with 1967VN028 processors. The results show that 1967VN028 meets the stated specifications and demonstrates computational efficiency similar to the ADSP-TS201 at a lower clock frequency. This can be achieved thanks to a two times greater number of parallel multiply-accumulate operations. The module demonstrated high efficiency on the presented control task of processing probing pulses. 2. Bobrov D.Yu., Dobrozhanskij A.P., Zajcev G.V., Malikov Yu.V., Cypin I.B. Cifrovaya obrabotka signalov v MRLS. Chast 2: algoritmy obrabotki radiolokacionnyh signalov // Cifrovaya obrabotka signalov. 2002. ¹ 1. pp. 28-39. 3. Bobrov D.Yu., Dobrozhanskij A.P., Zajcev G.V., Malikov Yu.V., Cypin I.B. Cifrovaya obrabotka signalov v MRLS. Chast 3 // Cifrovaya obrabotka signalov. 2002. ¹ 2. pp. 42-50. 4. Krasnobrov D., Ravko V. Cifrovaya obrabotka signalov - novoe reshenie // Elektronika NTB. 2017. ¹ 5. pp. 44-48. 5. Bakulev P.A. Radiolokatsionnyye sistemy: ucheb. dlya vuzov [Radar systems: textbook for universities]. Moscow, Radiotekhnika Publ. 2015. 440 p. (In Russian). 6. TigerSHARC Embedded Processor ADSP-TS201S. Data sheet. Analog Devices, Inc. 2006. https://www.analog.com/media/en/technical-documentation/data-sheets/AD-SP_TS201S.pdf. 7. Specification for 1967VN028. JSC "ICC "Milandr". 2021. https://ic.milandr.ru/upload/iblock/556/g5zyamzsnf6h8c1jmare6avuyds0ov2h/1967%D0%92%D0%9D028.pdf. 8. Programming Manual for 1967VN028 and 1967VN044. JSC "ICC "Milandr". 2021. https://ic.milandr.ru/upload/iblock/77f/77fac90e79704374aaccc4b44f3244d6.pdf. 9. Biblioteki funkcij cifrovoj obrabotki signalov DSPlib i standartnyh funkcij clib. Opisanie funkcij. JSC "ICC "Milandr". 2019. 10. Vityazev S.V. Programmnaya realizaciya cifrovogo filtra-decimatora na cifrovyh signalnyh processorah TigerSHARC ADSP-TS101 // Cifrovaya obrabotka signalov i ee primenenie. Trudy mezhdunar. nauch-tekhn. konf. Vyp.: XII-2. M.: 2010. pp. 259-261. 11. Vityazev S.V. Cifrovye processory obrabotki signalov. Kurs lekcij. M.: Goryachaya liniya - Telekom, 2017. - 100 p. If you have any question please write: info@dspa.ru |