Demodulation of Energy Hidden Linear-Frequency-Modulated Signals

Authors

DOI:

https://doi.org/10.20535/RADAP.2021.86.45-51

Keywords:

demodulation, linear-frequency-modulated signal, autocorrelation algorithm, a priori uncertainty, energy latent signal, correlation method, radio monitoring, complex signal, broadband signal

Abstract

Statement of the problem in general

Recently, there has been a tendency to increase the number of telecommunications systems that use spread spectrum signals: binary phase-shift keying (BPSK) signals with linear frequency modulation, chirp signals and their combinations. Due to this, the anti-jamming of telecommunication systems is increased, the stealth mode of their functioning is provided.

This tendency raises issues in the field of radio monitoring systems implementation. The use of spread-spectrum signals in telecommunication systems significantly reduces the spectral height of radio emission and their energy availability. Detection such radio emission, classifying the signals, measuring their parameters and demodulation in the absence of any information about the signals of telecommunication systems, is a complex scientific and technical task.

Analysis of recent research and publications

One of the important scientific and technical task in the direction of research of telecommunication systems radiomonitoring problems that use signals with linear frequency modulation (chirp signals), is demodulation of such signals in the conditions of uncertainty.

Previously, scientists solved the problem of detecting an energetically hidden chirp signal, determining its parameters using a discrete model of an autocorrelation receiver with quadrature processing and recognizing linear frequency modulation based on an autocorrelation receiver with double quadrature processing. Therefore, the problem of demodulation of energetically hidden signals with linear frequency modulation should be solved using the obtained scientific results as much as possible.

The scientific literature does not sufficiently cover the issue of demodulation of energetically hidden chirp signals of telecommunication systems in conditions of a priori uncertainty about the type and parameters of the signal and energetic concealment.

Thus, the relevance of the article is determined by its purpose, which is to develop a methodological apparatus for demodulation (recognition of the type of frequency) of energy-hidden chirp signals of telecommunications systems based on the autocorrelation method.

Presenting the main material

The article analyzes the uncertainty diagram of a rectangular chirp radio pulse. Characteristic features and cross-sectional features of the uncertainty diagram are revealed. An approach to demodulation of received energetically hidden chirp signals based on the use of the features of the uncertainty diagram of the elementary radio pulse is proposed. The possibility of their demodulation is substantiated. Simulation of the remodeling procedure was performed using Matlab R2016a and MathCAD 14 software packages. The simulation results confirm the ability of the proposed algorithm to demodulate chirp signals in the input combination at low signal-to-noise ratios.

Conclusion

To solve the problem of demodulation of chirp signals of telecommunication systems, an approach based on the results of the analysis of the location of the elliptical uncertainty diagram is used.

The sequence of steps for demodulation of chirp signals is determined.

It is established that the proposed autocorrelation algorithm with double quadrature processing is able to demodulate a chirp signal in the input combination with a signal-to-noise ratio of less than one.

The simulation results show that during the accumulation of 10-3 s it is possible to demodulate the binary symbols of the chirp signal with base 104 at a signal-to-noise ratio of minus 17 dB with a probability of error of 10-2.

Prospects for further development of the study

In the future, it is advisable to explore the possibility of recognizing other signals (BPSK), which can be used in the energy-hidden mode of telecommunications systems.

References

Перелік посилань

Horai M., Kobayashi H., Nitta T. Chirp Signal Transform and Its Properties / Hindawi. Journal of Applied Mathematics. — Vol. 2014. — Article ID 161989. — 2014. — 8 p. https://doi.org/10.1155/2014/161989.

Варакин Л. Е. Системы связи с шумоподобными сигналами. М.: Радио и связь, 1985. — 384 с. eLIBRARY ID: 24256018.

Стейскал А. Б., Ковтун С. О., Ільяшов О. О., Войтко В. В. Розпізнавання енергетично прихованих ЛЧМ сигналів телекомунікаційних систем в умовах параметричної невизначеності // Вісті вищих учбових закладів. Радиоэлектроника. — НТУУ ''КПИ''. — 2020. — T.63, №8 — C. 476–482. https://doi.org/10.20535/S0021347020080026.

Стейскал А. Б. Результати моделювання схеми визначення середньої частоти лінійно-частотно-модульованого сигналу з низькою спектральною щільністю потужності / А. Б. Стейскал // Сучасні інформаційні технології у сфері безпеки та оборони. — 2018. — Вип. 1(31). — С. 109–114.

Борисов В. И. Помехозащищённость систем радиосвязи с расширением спектра сигналов модуляцией несущей псевдослучайной последовательностью / В. И. Борисов, В. М. Зинчук, А. Е. Лимарев. – М. : Радио и связь, 2003. – 640 с.

Proakis J. C., Manolakis D. K. Digital Signal Processing (4th Edition) // Pearson. — 2006. — 1104 p.

Бакулев П. А. Радиолокационные системы: учеб. для вузов / П. А. Бакулев. — М.: Радиотехника, 2004. — 320 с.

Bondarenko V. N., Bogatyrev E. V., Krasnov T. V., Garifullin V. F. Noise immunity of a quasi-optimal correlation receiver of noiselike signals with minimum frequency-shift keying / Journal of Communications Technology and Electronics. — 2013. — Vol. 58. — P. 1194–1199. DOI: https://doi.org/10.1134/S1064226913070048.

Joneidi M., Zaeemzadeh A., Rezaeifar S., Abavisani M., Rahnavard N. LFM signal detection and estimation based on sparse representation // 2015 49th Annual Conference on Information Sciences and Systems (CISS), Baltimore, MD, USA. — 2015. — PP. 1-5. DOI: 10.1109/CISS.2015.7086856.

Chen R. and Wang Y. Universal FRFT-based algorithm for parameter estimation of chirp signals // Journal of Systems Engineering and Electronics. — 2012. — Vol. 23, Iss. 4. — PP. 495-501. https://doi.org/10.1109/JSEE.2012.00063.

Kolchev A. A., Nedopekin A. E. Application of model of mixture of probabilistic distributions for definition of the signals of radiophysical probing // Radioelectronics and Communications Systems. — 2016. — Vol. 59. — PP. 362-368. https://doi.org/10.3103/S0735272716080057.

Щербаков В. С. Корреляционно-фильтровой метод обработки сверхширокополосных ЛЧМ сигналов / В. С. Щербаков // Журнал радиоэлектроники. — 2018. — №2. — 18 c. http://jre.cplire.ru/jre/feb18/11/text.pdf.

IEEE Standard for Information technology – Telecommunications and information exchange between systems – Local and metropolitan area networks – Specific requirements. Part 15.4: Wireless Medium Access Control (MAC) and Physical Layer (PHY) Specifications for Low-Rate Wireless Personal Area Networks (WPANs) // IEEE Std 802.15.4a™-2007. – New York, USA, 2007.

References

Horai M., Kobayashi H., Nitta T. (2014). Chirp Signal Transform and Its Properties. Hindawi. Journal of Applied Mathematics, Vol.2014, Article ID 161989, 8 p. DOI: 10.1155/2014/161989.

Varakin L. Ye. (1985). Sistemy svyazi s shumopodobnymi signalami. M.: Radio i svyaz', 384 s. eLIBRARY, ID: 24256018. [In Russian].

Steiskal A. B., Kovtun S. O., Iliashov O. A., Voitko V. V. (2020). Identification of energy-hidden chirp signals of telecommunication systems in conditions of parametric uncertainty. Radioelectronics and Communications Systems, Vol. 63, No. 8, pp. 398-404. DOI: 10.3103/S0735272720080026.

Steiskal A. B. (2018). The results of scheme’s design of detecting middle frequency of energy-hidden chirp signals. Modern Information Technologies in the Sphere of Security and Defence, Vol 1(31), pp. 109–114. [In Ukrainian].

Borisov V. I., Zinchuk V. M., Limarev A. Ye. (2003). Pomekhozashchishchonnost' sistem radiosvyazi s rasshireniyem spektra signalov modulyatsiyey nesushchey psevdosluchaynoy posledovatel'nost'yu. M. : Radioisvyaz', 640 p. [In Russian].

Proakis J. C., Manolakis D. K. (2006). Digital Signal Processing, (4th Edition). Pearson, 1104 p.

Bakulev P. A. (2004). Radiolokatsionnyye sistemy: ucheb. dlyavuzov. M.: Radiotekhnika, 320 p. [In Russian].

Bondarenko, V. N., Bogatyrev, E. V., Krasnov, T. V., Garifullin, V. F. (2013). Noise immunity of a quasi-optimal correlation receiver of noiselike signals with minimum frequency-shift keying. Journal of Communications Technology and Electronics, Vol. 58, pp. 1194–1199. DOI: 10.1134/S1064226913070048.

Joneidi M., Zaeemzadeh A., Rezaeifar S., Abavisani M., Rahnavard N. (2015). LFM signal detection and estimation based on sparse representation. 2015 49th Annual Conference on Information Sciences and Systems (CISS), Baltimore, MD, USA, pp. 1-5. DOI: 10.1109/CISS.2015.7086856.

Chen R. and Wang Y. (2012). Universal FRFT-based algorithm for parameter estimation of chirp signals. Journal of Systems Engineering and Electronics, Vol. 23, Iss. 4, pp. 495-501. doi: 10.1109/JSEE.2012.00063.

Kolchev A. A., Nedopekin A. E. (2016). Application of model of mixture of probabilistic distributions for definition of the signals of radiophysical probing. Radioelectronics and Communications Systems, Vol. 59, pp. 362–368. DOI:10.3103/S0735272716080057.

Shcherbakov V. S. (2018). Korrelyatsionno-fil'trovoy metod obrabotki sverkhshirokopolosnykh LCHM signalov. Zhurnal radioelektroniki, No. 2. [In Russian].

IEEE Standard for Information technology -- Telecommunications and information exchange between systems -- Local and metropolitan area networks -- Specific requirements. Part 15.4: Wireless Medium Access Control (MAC) and Physical Layer (PHY) Specifications for Low-Rate Wireless Personal Area Networks (WPANs). IEEE Std 802.15.4a™-2007.

Published

2021-09-30

How to Cite

Стейскал , А. Б., Ковтун , С. О., Войтко , В. В. and Огарок , А. П. (2021) “Demodulation of Energy Hidden Linear-Frequency-Modulated Signals”, Visnyk NTUU KPI Seriia - Radiotekhnika Radioaparatobuduvannia, (86), pp. 45-51. doi: 10.20535/RADAP.2021.86.45-51.

Issue

Section

Telecommunication, navigation, radar systems, radiooptics and electroacoustics