Carrier Frequency Of Signal Research Articles

Highly secure non-orthogonal multiple access with key accompanying transmission based on subcarrier-indexed modulation.

This paper proposes a key-accompanying transmission scheme based on subcarrier indexed modulation (SIM). The key is used to control the activation state of subcarriers, with key masking achieved through the position information of silent subcarriers, which enables the cooperative transmission of both key and primary messages. Meanwhile, a four-dimensional hyperchaotic model is adopted to ensure system security. By utilizing power multiplexing, the scheme realizes the parallel transmission of two signals and disrupts the carrier frequency and symbol of the original signals. The scheme is experimentally demonstrated with a 54.25 Gb/s SIM-chaotic power division multiplexing (CPDM) signal transmission over 2 km of 7-core fiber.. The results indicate that the proposed scheme does not degrade system transmission performance at either high or low power levels. At the limit of forward error correction (FEC)=3.8×10-3, the impact of our scheme on receiver sensitivity is no greater than 0.1 dB. The accuracy and sensitivity of the key are maintained, with the transmission performance of the key remaining excellent. The bit error rate (BER) for the main signal is consistently kept at 0, while the BER for the key rises to around 0.5 if the key is misaligned by one bit. Moreover, the key space can reach 10135, effectively verifying the system's high security.

Virtual Array-Based Signal Detection and Carrier Frequency Offset Estimation in a Multistatic Collaborative Passive Detection System

To tackle the problem of difficult signal detection and carrier frequency synchronization faced by wireless communication among stations of the multistatic passive detection system in interference environments, an adaptive signal detection and carrier frequency offset (CFO) estimation method based on a virtual array is proposed in this paper. This is a data-aided method that utilizes a training sequence composed of three segments of sub-training sequences with different symbols. This method first uses spatial spectrum estimation to obtain the coarse frequency estimations of interference signals and CFO from virtual array signals constructed from the first two sub-training sequences. Then, beamforming is conducted accordingly on the virtual array signals constructed from the third sub-training sequence to suppress the in-band interferences and protrude the expected signal. Finally, improved performance of signal detection and CFO estimation is obtained with the beamformed signals. Simulation experiments show that a missed detection probability as low as 1 × 10−4, with a false detection probability of 1 × 10−3, can be obtained under a signal-to-interference ratio (SIR) of −10 dB and Eb/N0 of 1 dB. Moreover, the proposed method can also simultaneously achieve a CFO estimation error that is lower than 3%, with the condition of Eb/N0 being as low as −5 dB under different SIRs. Simulation results validate the proposed method and demonstrate the promising application prospects of the proposed method in networked passive detection scenarios.

Investigating Intra-Pulse Doppler Frequency Coupled in the Radar Echo Signal of a Plasma Sheath-Enveloped Target

In detecting hypersonic vehicles, the radar echo signal is coupled with an intra-pulse Doppler frequency (I-D frequency) component caused by relative motion of a plasma sheath (PSh) and the vehicle, which can induce the phenomenon of a ghost target in a one-dimensional range profile. In order to investigate the I-D frequency generated by the relative motion of a PSh, this study transforms a linear frequency modulated (LFM) signal into a single carrier frequency signal based on echo signal equivalent time delay-dechirp processing and realizes high resolution and fast extraction of the I-D frequency coupled with the frequency-domain echo signal. Furthermore, by relying on the computation of the surface flow field of the RAMC-II Blunt Cone Reentry Vehicle, the coupled I-D frequency in the radar echo signal of a PSh-enveloped target under circumstances of typical altitudes and carrier frequencies is extracted and further investigated, revealing the variation law of I-D frequency. The key findings of this study provide a novel approach for suppressing anomalies in radar detection of PSh-enveloped targets as well as effective detecting and as robust target tracking.

Comparative Study of TLP250 and IR2132 Driver-Based Inverter for Induction Motor Driving

As time progresses, electric motors are used for industrial or commercial purposes. The need for a motor that is robust, simple, and easy to maintain has been answered by creating an induction motor that can handle the purpose. At the beginning of its use, induction motors were more often used at constant speeds. Using an inverter becomes one of the solutions at hand to control the induction motor. Nowadays, most inverters are controlled by the SPWM (Sinusoidal Pulse Width Modulation) method. This method can adjust the output voltage and frequency by setting the carrier signal's frequency value and the reference signal's amplitude. A driver circuit is needed to implement an SPWM-based inverter. This driver circuit is needed to isolate the power circuit from the controller. Moreover, this circuit is also used to increase the microcontroller output signal to trigger the IGBT gate switch. The IR2132 and TLP250 drivers are often used in three-phase inverter applications. These drivers have advantages and disadvantages. This paper discusses the capabilities of these two drivers when applied to a three-phase inverter that functions as an induction motor drive. This inverter-controlled induction motor is advantageous because it can be rotated at a nominal speed and frequency.

High–Speed Laser Modulation for Low–Noise Micro–Cantilever Array Deflection Measurement

In this paper, an innovative approach is introduced to address the noise issues associated with micro–cantilever array deflection measurement systems employing multiple lasers. Conventional systems are affected by laser mode hopping during switching, resulting in wavelength instability and beam spot fluctuations that take several hundred milliseconds to stabilize. To mitigate these limitations, a high–speed laser modulation technique is utilized, leveraging the averaging effect over multiple modulation cycles within the sampling window. By driving the lasers with a high–frequency carrier signal, a low–noise and stable output suitable for micro–cantilever beam deflection measurement is achieved. The effectiveness of this approach is demonstrated by simultaneously modulating the lasers and rapidly observing the spectral and centroid variations during high–speed switching using a custom–built high–speed spectrometer. The centroid fluctuations are also analyzed under different modulation frequencies. The experimental results confirm that the high–speed modulation method can reduce the standard deviation of beam spot fluctuations by more than 90%, leading to significant improvements in noise reduction compared to traditional laser switching methods. The proposed high–speed laser modulation approach offers a promising solution for enhancing the precision and stability of multi–laser micro–cantilever array deflection measurement systems.

Influence of carrier signal frequency error on the demodulation phase of the fiber optic hydrophone

This paper investigates the influence of carrier signal frequency error on the demodulation phase of the fiber optic hydrophone with the demodulation algorithm of the phase generated carrier (PGC) and heterodyne. The proposed theory is demonstrated experimentally, with results showing that the frequency error between the carrier wave and local oscillator signal will influence the demodulated phase signal of the fiber optic hydrophone, which is consistent with the theory proposed. When the PGC algorithm is adopted, the error leads to a time-varying amplitude of the demodulated signal while a linear trend is superimposed on the signal demodulated by the heterodyne method.

A Coherent Integration Method for Moving Target Detection in Frequency Agile Signal-Based Passive Bistatic Radar

In this paper, the possibility of improving target detection performance in passive bistatic radar by exploiting a frequency agile (FA) signal is investigated, namely frequency agile signal-based passive bistatic radar (FAPBR) coherent integration. Since the carrier frequency of each pulse signal is agile, FAPBR coherent integration suffers from the problems of random range and Doppler phase fluctuations. To tackle these challenges, a novel FA signal coherent integration target detection scheme for PBR is proposed. In particular, the phase quadratic difference principle is presented for eliminating Doppler phase hopping. Then, frequency rearrangement is adopted to compensate for random range phase fluctuation while obtaining the high-range-resolution profiles (HRRPs) of the detecting target. Further, we innovatively present a sliding-range ambiguity decoupling (S-RAD) method to remove the range ambiguity effect in the case of the high pulse repetition frequency (HPRF). Compared with the existing methods, the proposed method can effectively mitigate Doppler phase hopping without requiring prior target velocity information, offering improved coherent integration performance in frequency agile signals with reduced computational complexity. Moreover, it successfully corrects the range ambiguity issue caused by HPRF. Finally, a series of simulation results are presented to demonstrate the effectiveness of the proposed algorithm.

Localized management of distributed flexible energy resources

The integration of distributed energy resources continues to be a challenge for the traditional electricity grid. Aside from additional variability in the net power demand, there is often a temporal discrepancy between generation and consumption schedules which can exacerbate demand peaks and troughs, leading to system overloading, voltage violations, and a low system load factor. This study proposes a control system approach to unify the management of the different types of flexible energy resources through Localized Demand Control. In this system, all flexible energy resources are coordinated using a power line carrier frequency signal to follow a preferred demand curve at the distribution transformer level. The system’s functionality has been confirmed in an actual 5-house microgrid without adverse effects on end-user comfort. Meanwhile, scaled-up simulation studies have shown improvements in the system load factor by as much as 189%, and increased hosting capacity by 40% for electric vehicles and 16% for solar photovoltaic panels.

Hardware-software complex for adjusting, monitoring and evaluating the accuracy characteristics of receivers for instantaneous measurement of the carrier frequency of a microwave signal

Hardware-software complex for adjusting, monitoring and evaluating the accuracy characteristics of receivers for instantaneous measurement of the carrier frequency of a microwave signal

Optical frequency comb assisted reconfigurable broadband spread spectrum signal generation.

A photonic-assisted scheme for spread spectrum communication signals generation is proposed and demonstrated in this article. The spreading sequence and the baseband data codes are modulated on the photonic link by electro-optic modulators, and the spread spectrum process is completed through stream processing on the analog microwave photonic link. By combining optical frequency comb and injection locking technologies, the carrier frequency of the communication signals can be tuned over an ultra-broadband range of 3-39 GHz. In the proof-of-concept experiments, spread spectrum signals at 3 GHz and 6 GHz are obtained with a spread factor of 31. The analysis results indicate that the generated signals possess excellent reconfiguration, anti-interference, and anti-interception properties. Overall, our proposed scheme offers a flexible photonic architecture with significant potential in the application of ultra-broadband covert communication systems.

Multi-task neural network for solving the problem of recognizing the type of QAM and PSK modulation under parametric a priori uncertainty

Objectives. Automatic modulation recognition of unknown signals is an important task for various fields oftechnology such as radio control, radio monitoring, and identification of interference and sources of radio emission. The paper aims to develop a method for recognizing the types of signal modulation under conditions of parametric a priori uncertainty, including the uncertainty of carrier frequency- and initial signal phase values. An additional task consists in estimating the offset values of the carrier frequency or signal phase at the initial stage of the recognition process.Methods. A multi-task learning with artificial neural network and the theory of cumulants of random variables are used.Results. For signals with a carrier frequency and initial phase shift, cumulant approaches for QAM-8, APSK-16, QAM-64, and PSK-8 modulations are calculated. A multi-task learning with artificial neural network using cumulant features and a data standardization algorithm is presented. The results of the experiment show that using multi-task learning with an artificial neural network provides high accuracy of recognizing QAM-8 and APSK-16, QAM-64 and PSK-8 modulations with small mismatches of the carrier frequency or initial phase. The accuracy of determining the offset values from the carrier frequency or the initial phase for QAM-8, APSK-16, QAM-64, and PSK-8 modulation is high.Conclusions. The multi-task learning with neural network using high-order signal cumulants makes it possible not only to recognize modulation types with high accuracy under conditions of a priori uncertainty of signal parameters, but also to determine the offset values of carrier frequency or initial signal phase from expected values.

IMPROVEMENT OF THE METHODOLOGY FOR EVALUATING THE CARRIER FREQUENCY OF THE SIGNAL DURING DATA TRANSMISSION IN TELECOMMUNICATION CONTROL AND DISTANCE LEARNING SYSTEMS

Effectiveness of the application of telecommunications systems is directly influenced by the effectiveness of the functioning of each component and device of its design. The article directly examines the issue of improving the carrier frequency estimation methodology for data transmission in telecommunication management and distance learning systems. The essence of the solution lies in proposals for improving the efficiency of frequency estimation at the input signal synchronization stage, which is presented on the example of a satellite telecommunication control system and distance learning. Namely, the analysis of modern satellite telecommunications systems was carried out and the features that affect the effectiveness of carrier frequency estimation and input signal synchronization were determined. The main inconsistencies are the low energy of the input signal receiving channel, significant signal frequency uncertainty, and the presence of "neighboring channels" receiving the input signal. It was determined that satellite communication systems during data transmission work in the mode with multi-station access in the variant of operation with frequency division of channels, which can receive data packets in the mode of multiple access or when providing a data reception channel on demand. At the same time, the operation of telecommunications systems can proceed both in continuous and in batch modes of receiving the input signal. It is considered that coherent processing of the input signal is carried out in demodulators of satellite telecommunications and interference-resistant coding is used. To solve the task of estimating the carrier frequency of the input signal in coherent demodulators of modern satellite telecommunications, considering the above-defined inconsistencies and features, the article proposes a methodical approach. The essence of this approach is to determine the potential boundary of variances of the obtained estimates of the carrier frequency and to develop algorithms for estimating the carrier frequency of the input signal separately for continuous and batch modes of input data transmission based on the fast Fourier transform. Keywords: Frequency, signal, uncertainty, carrier, estimation.

A Channel Compensation Technique Based on Frequency-Hopping Binary Offset Carrier Modulated Signal

Space-Air-GroundIntegrated Network (SAGIN) has been becoming a promising future network construction to enable the integration of terrestrial communications, aerial networks and satellite systems, for achieving high data rate wireless access and seamless coverage. Focusing on the space-to-air propagation, which is requiring transmitted signal of large Doppler shift resilience in dynamic circumstances, the proposed signal as employing I/Q modulation to accommodate frequency-hopping binary offset carrier (FH-BOC) signal and orthogonal frequency division multiplexing (OFDM) signal, and to exploit respective benefits. Finally, numeric results are provided to demonstrate performance superiority on Bit Error Rate (BER) and signal tracking stability. In conclusion, our designed signal requires about 8 dB less energy per bit at the desired BER level than normally compensated OFDM signal.

Wi-LADL: A Wireless-Based Lightweight Attention Deep Learning Method for Human–Vehicle Recognition

Wireless sensing-based human–vehicle recognition (HVR) methods have become a research hotspot due to their noninvasive, low-cost, and ubiquitous advantages. However, existing methods usually have limited applicability and low recognition performance. Furthermore, the antenna deployment height and the carrier frequency of wireless signals are also key factors that affect the HVR performance, but a few works deeply explore their impact on HVR tasks. To address these issues, inspired by the powerful feature learning capability of recently merged deep learning techniques, this article proposes an attention-based convolutional neural network (CNN) model named wireless-based lightweight attention deep learning (Wi-LADL) method for HVR. Wi-LADL takes received signal strength (RSS) as input since RSS contains the useful temporal feature of the gait for HVR. Wi-LADL consists of several lightweight CNN modules in series and a convolutional block attention module (CBAM) to learn high-level features from RSS signals. Experimental results on the developed five-category RSS dataset show that the proposed Wi-LADL not only achieves higher accuracy but also exhibits lower computational complexity compared with state-of-the-art HVR methods. In particular, Wi-LADL obtains the best performance with an average accuracy of 98.8% at the 2.4-GHz band and an antenna height of 0.8 m on HVR tasks. Specifically, when classifying one-pedestrian, two-pedestrians, one-bicycle, two-bicycles, and one-car, the proposed method achieves the recognition accuracy of 97.06%, 97.14%, 100%, 100%, and 100%, respectively. To facilitate the development of wireless sensing technology, the developed new RSS dataset has been publicly available at <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/TZ-mx/WiParam</uri> .

Information embedding in DFRC networks through chirp waveform diversity

We consider a dual function radar communications network and propose a waveform diversity-based approach to embed both target and scheduling data in the transmitter pulses. The scheduling data of radar signal bandwidth, carrier frequency, and waveform along with the information on target detection, range, and Doppler are shared among the network radar nodes without a need for designated communication links. Scheduling and target information are encoded to bits and transmitted over the radar coherent processing interval using up- and down-chirps. We derive exact expressions of probability of bit error and false alarm rate for sharing scheduling and target information data between two radar nodes. The effect of different parameters and data sharing on the radar performance is analyzed and validated by computer simulations. Using the cross-ambiguity function, we show the capability of the up- and down- chirp sequence transmission scheme in reducing range sidelobes compared to the conventional transmission of only the up- (or down-) chirps. To overcome the limited data rate associated with only using two chirp waveforms, we consider orthogonal chirp division multiplexing and derive its CAF. We demonstrate the suitability of OCDM for high data rate radar operations by examining the mainlobe width and sidelobe levels of the zero-Doppler and zero-delay cuts of the CAF.

CZT Algorithm for the Doppler Scale Signal Model of Multireceiver SAS Based on Shear Theorem

In multireceiver synthetic aperture sonars (SASs), the traditional non-stop-hop-stop model normally ignores the intrapulse motion of sonar platform. However, such intrapulse motion brings the Doppler scale effect (DSE) to the echo signal, which will lead to the change in carrier frequency (CF) and frequency modulation (FM) rate of echo signal and may eventually result in image defocus. In this article, considering the intrapulse motion, the time-varying time delay and range history of multireceiver SAS were derived by introducing the range time into the range history, and then the Doppler scale signal model was established. After approximating the derived time-varying range history, the 2-D spectrum was derived by using the shear theorem. When compared with the traditional 2-D spectrum, an interesting phenomenon was found that the change in FM rate has no effect on the 2-D spectrum. Actually, only two additional terms, i.e., range cell migration (ARCM) and azimuth modulation (AAM), were introduced into the new 2-D spectrum due to the change in CF. Besides, the condition of neglecting the ARCM was given by further analyzing the 2-D spectrum, while the AAM is usually small and can be easily compensated together with the ARCM correction. Finally, a chirp-z transform (CZT) algorithm for the Doppler scale signal model was proposed to correct the ARCM, which can simultaneously correct the ARCM and compensate the AAM (although not required) in the 2-D frequency domain by phase multiplication. The effectiveness of the signal model and the proposed algorithm is verified by simulations and field data.

Knowledge-Enhanced Compressed Measurements for Detection of Frequency-Hopping Spread Spectrum Signals Based on Task-Specific Information and Deep Neural Networks

The frequency-hopping spread spectrum (FHSS) technique is widely used in secure communications. In this technique, the signal carrier frequency hops over a large band. The conventional non-compressed receiver must sample the signal at high rates to catch the entire frequency-hopping range, which is unfeasible for wide frequency-hopping ranges. In this paper, we propose an efficient adaptive compressed method to measure and detect the FHSS signals non-cooperatively. In contrast to the literature, the FHSS signal-detection method proposed in this paper is achieved directly with compressed sampling rates. The measurement kernels (the non-zero coefficients in the measurement matrix) are designed adaptively, using continuously updated knowledge from the compressed measurement. More importantly, in contrast to the iterative optimizations of the measurement matrices in the literature, the deep neural networks are trained once using task-specific information optimization and repeatedly implemented for measurement kernel design, enabling efficient adaptive detection of the FHSS signals. Simulations show that the proposed method provides stably low missing detection rates, compared to the compressed detection with random measurement kernels and the recently proposed method. Meanwhile, the measurement design in the proposed method is shown to provide improved efficiency, compared to the commonly used recursive method.

A fast TDOA and VDOA estimation method of the wideband frequency hopping signal

In the mobile multi-station passive positioning scenario, the carrier frequency hopping of the wideband frequency hopping communication signal will produce a changing Doppler frequency shift. Therefore, it is not possible to directly estimate the Doppler frequency difference of the observed signal containing multiple pulses. In this case, only the time difference and frequency difference of the single-hop signal can be estimated, but the accuracy is low. The existing methods often need the carrier frequency of each FH pulse signal as a priori information, and the high computational complexity of the two-dimensional search method of the time difference and frequency difference is difficult to overcome. Aiming at the above problems, a fast and high-precision estimation algorithm for the time difference of arrival and velocity difference of wideband frequency hopping signals is proposed in this paper. Firstly, the wideband frequency hopping signal is segmented in the time domain with multiple pulses as the unit, the signal model of time-varying time difference is established, and the time difference of each short-time segment is estimated by the generalized cross-correlation algorithm. The estimated values of the initial time difference and Doppler velocity difference can be worked out by least squares fitting of the time difference sequence obtained from the single pulse estimation. Finally, taking the Link16 data link signal as an example, the simulation experiment of the proposed method is conducted, which verifies the correctness and performance superiority of the algorithm.

Research and Analysis on the Cultivation of Intelligent Transportation Technology Professionals under the Background of Integration of Production and Education

In order to improve the training effect of transportation technology professionals, this paper combines the intelligent digital signal processing method to process the data of the integration of production and education, and explores the training process of transportation technology professionals. In the process of data processing of industry-education fusion, this paper demodulates the nuclear magnetic resonance signal obtained after A/D conversion from the carrier frequency signal and places it at zero frequency. At the same time, this paper realizes the separation of the real part and the imaginary part of the nuclear magnetic resonance signal and constructs the digital sine table and digital cosine table of the carrier reference frequency. In addition, the data output by the ADC is subjected to quadrature detection to become two data signals, which are the in-phase component and the quadrature component. Finally, this paper constructs an intelligent analysis model. The simulation results show that the talent training method of intelligent transportation technology based on the integration of production and education has good effects, which can effectively improve the training effect of transportation technology professionals.

Design of Multi-Parameter Compound Modulated RF Stealth Anti-Sorting Signals Based on Hyperchaotic Interleaving Feedback.

Radio frequency (RF) stealth anti-sorting technology is a research hotspot in the radar field. In this study, the signal design principles of anti-cluster and anti-SDIF sorting were investigated for processes of clustering pre-sorting and sequence-difference-histogram main sorting. Then, in accordance with the signal design principle, a 2D interleaving feedback hyperchaotic system based on the cosine-exponential was designed. A method to modulate the pulse repetition interval (PRI) of the signal parameters and carrier frequency with wide intervals through the hyperchaotic system was developed. Finally, we verified the correctness of the signal design principle, the performance of the hyperchaotic system, and the anti-sorting performance of the designed signal using simulations. The results showed that the signal design principle could guide the signal design. The hyperchaotic system outperformed the classical 1D and 2D chaotic systems and the classical 3D Lorenz systems in terms of randomness and complexity. Anti-cluster sorting and anti-SDIF sorting could be realized by anti-sorting signals modulated by a hyperchaotic system, with the anti-SDIF sorting performance being better than that of the PRI random jitter signal.