Usable Frequency Research Articles

A Frequency Selecting Method for High-Frequency Communication Based on Ionospheric Oblique Backscatter Sounding

Ionospheric oblique backscatter sounding is an effective means of monitoring the ionosphere which can be used as a frequency selection system to serve HF communication and ensure its quality and stability. But how to obtain effective information from the oblique backscatter ionogram is still a hot issue. Due to this situation, a frequency selecting method for HF communication based on ionospheric oblique backscatter sounding is proposed in this study. After obtaining the ionograms, pattern recognition is used to separate the vertical echoes and the oblique backscatter echoes. Next, the leading edge of the oblique backscatter echoes are extracted, and then a two-dimensional electron density profile can be reconstructed. Then, with the help of ray tracing, the usable frequency range can be estimated. Finally, according to the signal-to-noise ratio reflected by the ionograms, several optimal communication frequencies can be selected. In order to verify this method, oblique ionograms are obtained through oblique sounding experiments to evaluate its accuracy. The result indicates that the usable frequency range and the selected frequencies are in accordance with the echo of the oblique ionogram, so the practicability and accuracy of the method are validated. Eventually, the maximum usable frequencies (MUFs) obtained from oblique backscatter sounding are compared with the MUFs from the oblique sounding ionogram; its Mean Absolute Percentage Error (MAPE) is 7.8% and its root mean squared error (RMSE) is 1.34 MHz.

Adaptation of a Differential Scanning Calorimeter for Simultaneous Electromagnetic Measurements.

Although much information can be gained about thermally induced microstructural changes in metals through the measurement of their thermophysical properties using a differential scanning calorimeter (DSC), due to competing influences on the signal, not all microstructural changes can be fully characterised this way. For example, accurate characterisation of recrystallisation, tempering, and changes in retained delta ferrite in alloyed steels becomes complex due to additional signal changes due to the Curie point, oxidation, and the rate (and therefore the magnitude) of transformation. However, these types of microstructural changes have been shown to invoke strong magnetic and electromagnetic (EM) responses; therefore, simultaneous EM measurements can provide additional complementary data which can help to emphasise or deconvolute these complex signals and develop a more complete understanding of certain metallurgical phenomena. This paper discusses how a DSC machine has been modified to incorporate an EM sensor consisting of two copper coils printed onto either side of a ceramic substrate, with one coil acting as a transmitter and the other as a receiver. The coil is interfaced with a custom-built data acquisition system, which provides current to the transmit coil, records signals from the receive coil, and is controlled by a graphical user interface which allows the user to select multiple excitation frequencies. The equipment has a useable frequency range of approximately 1-100 kHz and outputs phase and magnitude readings at a rate of approximately 50 samples per second. Simultaneous DSC-EM measurements were performed on a nickel sample up to a temperature of 600 °C, with the reversable ferromagnetic to paramagnetic transition in the nickel sample invoking a clear EM response. The results show that the combined DSC-EM apparatus has the potential to provide a powerful tool for the analysis of thermally induced microstructural changes in metals, feeding into research on steel production, development of magnetic and conductive materials, and many more areas.

A Spatial Reconstruction Method of Ionospheric foF2 Based on High Accuracy Surface Modeling Theory

The ionospheric F2 critical frequency (foF2) is one of the most crucial application parameters in high-frequency communication, detection, and electronic warfare. To improve the accuracy of spatial reconstruction of the ionospheric foF2, we propose a high-accuracy surface (HAS) modeling method. This method converts difficult-to-solve differential equations into more manageable algebraic equations using direct difference approximation, significantly reducing algorithm complexity and computational load while exhibiting excellent convergence properties. We used seven stations in Brisbane, Canberra, Darwin, Hobart, Learmonth, Perth, and Townsville, with one station as a validation station and six as training stations (e.g., Brisbane as a validation station and the other stations—Canberra, Darwin, Hobart, Learmonth, Perth, and Townsville—as training stations). The training stations and the HAS method were used to train and reconstruct the validation stations at different solar activity periods, seasons, and local times. The predicted values of the validation stations were compared with the measured values, and the proposed method was analyzed and validated. The reconstruction results show the following. (1) The relative root mean square errors (RRMSEs) of HAS method prediction in different solar activity epochs were 13.67%, 7.74%, and 9.19%, respectively, which are 13.57%, 7.41%, and 6.41% higher than the prediction accuracy of the Kriging method, respectively. (2) In the four seasons, the RRMSEs of the HAS method prediction are 9.27%, 13.1%, 8.81%, and 8.09%, respectively, which are 10.83%, 11.73%, 4.25%, and 12.00% higher than the prediction accuracy of the Kriging method. (c) During the daytime and nighttime, the RRMSEs of HAS method prediction were 9.23% and 11.17%, which were 5.92% and 11.99% higher than the prediction accuracy of the Kriging method, respectively. (d) Under the validation dataset, the average predictive RRMSE of the HAS method was 10.29%, and the average predictive RRMSE of the IRI prediction model was 12.35%, with a 2.06% improvement in the predictive accuracy of the HAS method. In general, the prediction effect of the HAS method was better than that of the Kriging method, thus verifying the effectiveness and reliability of the proposed method. In summary, the proposed reconstruction method is of great significance for improving usable frequency prediction and enhancing communication performance.

Assessment of IRI2020 model accuracy in predicting ionospheric parameters: Insights from multiple ionosonde stations

This research assesses the performance of the IRI2020 model in forecasting the ionospheric critical frequency of the F2 layer (foF2) and Maximum Usable Frequency (MUF) of the ionosphere from 2020 to 2023 across multiple ionosonde stations. The primary objective is to analyse the characteristics of foF2 and MUF across various longitudinal sectors during the solar minimum to ascending phase of solar cycle 25 and to evaluate the IRI2020 model’s performance in replicating observed data. Additionally, the study explores the influence of various space weather parameters on the variability of these ionospheric parameters. The findings reveal that the IRI2020 model overestimates the daily mean values of both foF2 and MUF(3000)F2 across the stations over the three years. While exhibiting good performance in capturing the pattern of hourly predictions, the model tends to overestimate foF2 more than MUF(3000)F2, with better predictions observed for MUF(3000)F2. However, hourly estimations display a mix of underestimation and overestimation, predominantly overestimating values. Correlations ranged from 0.58 to 0.92 for foF2 and 0.72 to 0.91 for MUF(3000)F2, showing variability across stations. As solar activity increases, seasonal variations become more evident, especially in stations located in the northern hemisphere.In contrast, stations in the southern hemisphere exhibit less pronounced seasonal variations, suggesting a notable hemispheric asymmetry. Although the IRI2020 better captured the general trend of foF2 and MUF(3000)F2 in our investigation, the percentage deviation for MUF(3000)F2 ranges from 1 % to 15.1 %, which can result in a significant range reduction for practical applications like HF communications. Stations closer to the geomagnetic equatorial line exhibit stronger seasonal asymmetry and higher deviations. Some key space weather parameters, including sunspot number R, F10.7 and R/F10.7 ratio, were found to significantly influence ionospheric variability, with sunspot number R and R/F10.7 showing a stronger correlation with foF2 and MUF(3000)F2. These suggest that the variability of the solar active region parameters primarily controls ionospheric foF2 and MUF(3000)F2.

Extraction of Underwater Acoustic Signals across Sea–Air Media Using Butterworth Filtering

Direct wireless communication through sea–air media is essential for constructing an integrated communication network that spans space, air, land, and sea. The amplitude of acoustically induced micromotion surface waves is much smaller than the noise interference in complex sea states, making the accurate extraction of these signals from the raw signals detected by an FMCW millimeter-wave radar a major challenge. In this paper, Butterworth filtering is used to extract underwater acoustic signals from the surface waves detected by radar. The physical processes of the channel were simulated theoretically and verified experimentally. The results demonstrate a fitting coefficient of 0.99 between the radar-detected water surface waves and the simulation outcomes, enabling the effective elimination of noise interference and the extraction of acoustically induced micromotion signals in environments with a signal-to-noise ratio (SNR) of −20 dB to −10 dB. Experiments modifying frequency and linear frequency modulation have verified that the usable frequency range for underwater acoustic signals is at least 400 Hz, meeting the frequency requirements of Binary Frequency Shift Keying (2FSK) modulation encoding methods. This research confirms the accuracy of the simulation results and the feasibility of filtering and extracting underwater acoustic signals, providing a theoretical basis and an experimental foundation for building cross-media communication links.

Usability of Community Seismic Network recordings for ground-motion modeling

A source of ground-motion recordings in urban Los Angeles that has seen limited prior application is the Community Seismic Network (CSN), which uses low-cost, micro–electro–mechanical system (MEMS) sensors that are deployed at much higher densities than stations for other networks. We processed CSN data for the 29 earthquakes with M > 4 between July 2012 and January 2023 that produced CSN recordings, including selection of high- and low-pass corner frequencies ( fcHP and fcLP, respectively). Each record was classified as follows: (1) Broadband Record (BBR)—relatively broad usable frequency range from fcHP < 0.5 to fcLP > 10 Hz; (2) Narrowband Record (NBR)—limited usable frequency range relative to those for BBR; and (3) Rejected Record (REJ)—noise-dominated. We compare recordings from proximate (within 3 km) CSN and non-CSN stations (screened to only include cases of similar surface geology and favorable CSN instrument housing). We find similar high- to medium-frequency ground motions (i.e. peak ground acceleration (PGA) and Sa for T < 5 s) from CSN BBR and non-CSN stations, whereas NBRs have lower amplitudes. We examine PGA distributions for BBR and REJ records and find them to be distinguished, on average across the network, at 0.005 g, whereas 0.0015 g was found to be the threshold between usable records (BBR and NBR) and pre-event noise. Recordings with amplitudes near or below these thresholds are generally noise-dominated, reflecting environmental and anthropogenic ground vibrations and instrument noise. We find nominally higher noise levels in areas of high-population density and lower noise levels by a factor of about 1.5 in low-population density areas. By applying the 0.0015 g threshold, limiting distances for the network-average site condition, based on the expected fifth-percentile ground-motion levels, are 89, 210, 280, and 370 km for M 5, 6, 7, and 8 events, respectively.

Моделирование КВ-радиотрасс на основе волноводного подхода

We present a scheme for modeling HF radio signal characteristics along paths of different lengths, which is based on the waveguide approach — the normal mode method. We use a representation of the recorded signal field in the form of Green function products of the angular operator, excitation coefficients, and reception coefficients of individual normal modes. Algorithms have been developed for calculating distance-frequency, frequency-angular, and amplitude characteristics of signals in large spatial regions through analysis and numerical summation of normal mode series. We have implemented a complex algorithm for simulating propagation conditions of HF radio signals, which includes a medium model, algorithms for calculating signal characteristics, and operational diagnostics of radio channel. We have compared the results of the HF signal propagation characteristic modeling and the experimental oblique sounding data obtained along paths of different lengths and orientation. To analyze experimental ionograms, determine the maximum usable frequencies for propagation modes along radio paths, we employ the method of automatic processing and interpretation of oblique sounding ionograms.

HF radio path modeling by waveguide approach

We present a scheme for modeling HF radio signal characteristics along paths of different lengths, which is based on the waveguide approach — the normal mode method. We use a representation of the recorded signal field in the form of Green function products of the angular operator, excitation coefficients, and reception coefficients of individual normal modes. Algorithms have been developed for calculating distance-frequency, frequency-angular, and amplitude characteristics of signals in large spatial regions through analysis and numerical summation of normal mode series. We have implemented a complex algorithm for simulating propagation conditions of HF radio signals, which includes a medium model, algorithms for calculating signal characteristics, and operational diagnostics of radio channel. We have compared the results of the HF signal propagation characteristic modeling and the experimental oblique sounding data obtained along paths of different lengths and orientation. To analyze experimental ionograms, determine the maximum usable frequencies for propagation modes along radio paths, we employ the method of automatic processing and interpretation of oblique sounding ionograms.

Impact of varying channel length on Analog/RF performances in a novel n-type silicon-based DG-JLT

Shrinking MOSFETs suffer performance hits due to short-channel effects and leakage. Junctionless transistors JLTs emerge as promising alternatives due to simpler fabrication and better gate control. This paper investigates the analog and RF performance characteristics of n-type Silicon-Based Double Gate Junctionless Transistors with varying channel lengths (15 nm, 20 nm, and 25 nm) This study evaluates analog device performance through critical parameters: drain current density (Id), transconductance (gm), output resistance (RO), intrinsic gain (gmRO), and transconductance generation factor (gm/Id). These parameters assess current handling, gain characteristics, and design efficiency, providing a comprehensive analysis for analog circuit applications. Results indicate that the device having 15 nm channel length exhibits a transconductance which is 25.38 % more than the 20 nm variant and drain current which is 44.7 % more than the latter, suggesting its superior performance to devices with longer channel lengths. In addition, the RF performance of the devices is evaluated using the small signal model of the device. This work further investigates the high-frequency response of the devices using key figures of merit (FoMs): gate capacitances (Cgs, Cgd, Cgg), cut-off frequency (fT), and maximum oscillation frequency (fMAX). These parameters quantify the influence of parasitic capacitances on switching speed and the maximum useable frequency for analog and RF applications. Analyzing Cgs, Cgd, and Cgg reveals the impact of gate control on high-frequency operation. The device having 15 nm channel length, exhibits an increase of 47.29 % in fT and 68.97 % increase in fMAX compared to device having 20 nm channel length. The findings underscore the significance of channel length optimization in enhancing the Analog and RF performance of n-type Silicon-based Double Gate Junctionless Transistors.

Comparison and validation of MOF observations and MUF predictions from seven different models

The prediction method of MUF (Maximum Usable Frequency) has been extensively deliberated as a pivotal technology in HF (High Frequency) communication. To verify the reliability of MUF prediction models commonly used in HF communications, we evaluated the prediction accuracy of seven typical prediction models based on maximum observed frequency (MOFs) and predicted MUFs. The oblique-sounding (OS) circuit was from Changchun to Jingyang, with the vertical-sounding (VS) station situated in Beijing which is, approximately at the midpoint of this oblique-sounding (OS) circuit. The RMSE (root mean square error) and RRMSE (relative root mean square error) between the MOFs and predicted MUFs by the model were used to evaluate the accuracy of the models. The results of statistical analysis show that: (a) the prediction results of the seven models are consistent with the observed results in trend, among which the prediction results of the Lockwood model (LWM), the nonuniform ionospheric conditions MUF calculation model (NYM), and the model proposed by Istituto Nazionale di Geofisica e Vulcanologia (INGV) are in good agreement with the observed results; (b) In the four seasons, the seasonal distribution of the seven models is significantly different, and the INGV model has a better prediction effect; (c) The INGV model is superior to other models in relatively high solar activity epochs and relatively low solar activity epochs, followed by the LWM model, with little difference between the two models and close prediction accuracy; (d) The INGV model has a better prediction result in four different periods of a day, and the improved simplified MUF calculation model (MSPM) has a great prediction result in the periods of nighttime.

A Short-Term Forecasting Method for High-Frequency Broadcast MUF Based on LSTM

This paper proposes a short-term forecasting method for high-frequency broadcast Maximum Usable Frequency (MUF) based on Long Short-Term Memory (LSTM) to meet the demand for refined and precise high-frequency broadcast coverage. Based on the existing infrastructure of broadcast and television stations, we established an experimental verification system to collect data for approximately three years. Two links were selected based on data quality: Urumqi to Lhasa and Lanzhou to Lhasa. A short-term forecast of MUF was conducted using the data from these two links. Comparison and analysis were conducted between the forecasting results of our model and those of the REC533 model. Our proposed method outperforms the REC533 forecasting results overall, with a reduction in root mean square error (RMSE) of 0.66 MHz and an improvement in forecast accuracy of 14.77%. The comparison result demonstrates the feasibility and accuracy of our model.

FPGA-Based High-Speed Energy-Efficient 32-Bit Fixed-Point MAC Architecture for DSP Application in IoT Edge Computing

Designing high-speed and energy-efficient blocks for image and digital signal processing (DSP) architecture is an evolving research field. This work designs a high-speed and energy-efficient multiply-accumulate (MAC) unit to augment the performance of field-programmable gate array (FPGA)-based accelerators and softcore processors. In this work, three discrete 32-bit fixed-point signed MAC architectures were designed in Verilog and synthesized for the Zynq 7000 ZedBoard to obtain efficient MAC architecture. The ultimate goal of this work is to design a fast and energy-efficient MAC unit that can achieve speed up to the DSP48 block to reduce the latency of IoT edge computing. Energy efficiency was achieved in PPG and partial product addition (PPA) for the proposed Booth radix-4 Dadda (BR4D)-based MAC. At PPG, the width of the partial product (PP) terms was optimized with Bewick’s signed extension to reduce the power consumption. At PPA, the number of PP rows reduces the critical path delay (CPD) with Dadda-based PPA. The proposed BR4D MAC unit offers a reduction in dynamic power, CPD, power-delay product (PDP) and energy-delay product (EDP) by 22%, 9%, 29% and 36%, respectively, compared to standard Booth radix-4 Wallace tree (BR4WT) based MAC. Furthermore, hybrid MACs (BR4WT and BR4D) were compared with the current state-of-the-art (SoA) designs, and it was found that the proposed BR4D MAC is 47% faster compared to the same design in SoA. The proposed BR4D was tested for frequency scaling technique by reducing the frequency in steps of 10 MHz from a maximum usable frequency (MUF) of 64 MHz to 10 MHz to evaluate the performance for low-power applications. Reducing clock frequency by 84% will reduce the power consumption at the same proportion and speed by 38%. Additionally, the proposed design helps to improve the battery life of IoT end nodes with a reduction in energy consumption and EDP by 76% and 61%, respectively.

PyIRI: Whole‐Globe Approach to the International Reference Ionosphere Modeling Implemented in Python

AbstractThe International Reference Ionosphere (IRI) model is widely used in the ionospheric community and considered the gold standard for empirical ionospheric models. The development of this model was initiated in the late 1960s using the FORTRAN language; for its programming approach, the model outputs were calculated separately for each given geographic location and time stamp. The Consultative Committee on International Radio (CCIR) and International Union of Radio Science (URSI) coefficients provide the skeleton of the IRI model, as they define the global distribution of the maximum useable ionospheric frequency foF2 and the propagation factor M(3,000)F2. At the U.S. Naval Research Laboratory, a novel Python tool was developed that enables global runs of the IRI model with significantly lower computational overhead. This was made possible through the Python rebuild of the core IRI component (which calculates ionospheric critical frequency using the CCIR or URSI coefficients), taking advantage of NumPy matrix multiplication instead of using cyclic addition. This paper explains in detail this new approach and introduces all components of the PyIRI package.

Development of a universal, machine tool independent dynamometer for accurate cutting force estimation in milling

When integrating a dynamometer into a machining system, it is necessary to identify the dynamic relationship between the effective input forces and the measured output signals (i.e., its transmissibility) through dedicated experimental modal analysis. Subsequently, a filter can be derived and applied to reconstruct the effective input forces from the measured signals. Unfortunately this identification phase can be complex, posing challenges to the device’s applicability in both laboratory and industrial conditions. Here this challenge is addressed by introducing a novel dynamometer concept based on both load cells and accelerometers, along with a Universal Inverse Filter. Notably, this filter is independent of the dynamic behavior of the mechanical system where the device is installed. A single calibration suffices, ideally conducted by the device manufacturer or by an expert, allowing the dynamometer’s integration by a non-expert user into any machining system without the need for repeating the identification phase and the filter generation. Furthermore, this new concept offers another significant advantage: it attenuates all inertial disturbances affecting the measured signals, including those arising from the cutting process and those originating from exogenous sources such as spindle rotation, linear axes’ movements, and other vibrations propagating through the machine tool structure. To illustrate, a simplified model is introduced initially, followed by an overview of the novel dynamometer design, innovative identification phase, and filter construction algorithm. The outstanding performance of the novel (non-parametric) Universal Inverse Filter – about 5 kHz of usable frequency bandwidth along direct directions and 4.5 kHz along cross dir. – was experimentally assessed through modal analysis and actual cutting tests, compared against state of the art filters. The efficacy of the new filter, which is even simpler than its predecessors, was successfully demonstrated for both commercial and taylor-made dynamometers, thus showing its great versatility.

Design and construction of the Texas Christian University impedance tube

The two-microphone impedance tube test method is a well-established and widely used technique for determining the acoustic absorption coefficient and impedance ratio of materials. This method uses two closely spaced microphones to simultaneously measure the incident and reflected sound waves. A two-microphone impedance tube measurement system made of 6061-T6 Aluminum with a diameter of 3 inches, a 0.5 inch wall thickness, and microphones spaced 2.7 inches apart has been constructed for undergraduate research at Texas Christian University (TCU). These geometrical values suggest a usable frequency range of 50 Hz to 2637.77 Hz as referenced in ASTM Standard E1050-19. Validation of the system was achieved by taking measurements on Owen Corning Type 705 pressed fiberglass board with a 1-inch thickness and comparing them to absorption data provided by the manufacturer. Additional validation measurements were taken without a test sample in place. All validation tests suggest that the TCU impedance tube is an accurate measurement system.

A unique SWB multi-slotted four-port highly isolated MIMO antenna loaded with metasurface for IOT applications-based machine learning verification

This study introduces a MIMO antenna system incorporating an epsilon negative Meta Surface (MS). The system’s architects intended for it to have a large usable frequency range, high gain, narrow inter-component spacing, and superior isolation properties with four elements of MIMO antenna that are strategically organized in an orthogonal arrangement and a compact form factor measuring 41 × 41 × 1.6 mm3, utilizing a low-loss Rogers RT5880 substrate. The architecture of the antenna is characterized by integrating a multi-slotted radiating patch, a partial ground plane, and an epsilon-negative Meta Surface. This integration is done by a 7 × 7 Metamaterial array at the back of the MIMO antenna with a dimension of 41 × 41 × 1.6 mm3, resulting in a collective enhancement of the antenna’s overall performance by affecting the phase, amplitude, electromagnetic field and reducing the backward radiation. The separation between the Meta-surface and the MIMO antenna is established at a distance of 6 mm. The antenna’s exceptional super wideband performance is increased from 2–19 GHz to 1.9–20 GHz after using the MS. Moreover, isolation increases from 20 dB to 25.5 dB, Realized gain from 4.5 dBi to 8 dBi, and radiation efficiency from 77% to 89% across the operational bandwidth. The MIMO antenna exhibits remarkable diversity characteristics, as indicated by an envelope correlation coefficient (ECC) of <0.004, a diversity gain (DG) surpassing 9.98 dB, a channel capacity loss (CCL) below 0.3, and a total active reflection coefficient (TARC) measuring 12 dB. Furthermore, a circuit analogous to a resistor–inductor–capacitor (RLC) system is constructed, and four regression methods from the field of machine learning are employed to validate the gain and efficiency achieved. Notably, the linear regression model exhibits exceptional performance, achieving an accuracy of 99%. The MIMO antenna design demonstrates significant potential for many applications in the Internet of Things (IoT), specifically focusing on Vehicle-to-Everything (V2X) communications. These highlight its appropriateness for emerging IoT sectors.

Preliminary Results of Methodology for Forecasting the Minimum Virtual Height of Ionospheric F-Region for Sofia City

Using the virtual height for the calculation of the minimum and maximum usable frequency of a given radio path is well known. The purpose of the present investigation is to illustrate a methodology for determining the values of the minimum virtual height (h’F) of the ionospheric F-region. The dependence of the entire ionosphere on the level of solar activity is one of the main factors in the empirical modelling of the ionosphere. Correlation analysis was used to assess the relationship between the quantities. The results show a significant correlation, confirming the well-known relationship between solar activity and its impact on the ionosphere. In order to analyze the most appropriate dependence between the solar activity represented by F107 and h’F, a regression analysis was performed by month. The results show that the optimal dependence is close to linear. As a result, an empirical median model for forecasting h’F for the territory of Sofia city, depending on solar activity and season, is proposed. In its concluding part, this study also presents examples of the model's performance in selected months. The resulting errors are ME=0.000 km and RMS=8.180 km, respectively, which is accurate enough for practical purposes.

Алгоритм автоматического определения максимально-применимых частот коротковолновых радиолиний и использование этой информации в системе управления комплекса радиосвязи

The article discusses algorithms for automatic determination of the maximum usable frequency (MUF). It is proposed to use special software (SPO) to determine the MUF.

Numerical Derivation of Design Guidelines for Tightness and Shaking Amplitude of Vibrating Intrinsic Reverberation Chamber by Method of Moment

Vibrating intrinsic reverberation chamber is being used as an in-situ EMC test equipment for large and complex systems such as automobiles and aircrafts. In this paper, the stirring conditions, such as tightness and shaking amplitude of the walls, of a vibrating intrinsic reverberation chamber have been analyzed using the method of moments. From the viewpoint of quantitative evaluation of the flexible moving walls configuration, it was found that the random electromagnetic environment can be generated under the stirring conditions of loose configuration and a shaking amplitude more than one eighth of the wavelength at the test frequency above the lowest usable frequency.

A Search for Technosignatures Around 11,680 Stars with the Green Bank Telescope at 1.15–1.73 GHz

We conducted a search for narrowband radio signals over four observing sessions in 2020–2023 with the L-band receiver (1.15–1.73 GHz) of the 100 m diameter Green Bank Telescope. We pointed the telescope in the directions of 62 TESS Objects of Interest, capturing radio emissions from a total of ∼11,680 stars and planetary systems in the ∼9′ beam of the telescope. All detections were either automatically rejected or visually inspected and confirmed to be of anthropogenic nature. We also quantified the end-to-end efficiency of radio SETI pipelines with a signal injection and recovery analysis. The UCLA SETI pipeline recovers 94.0% of the injected signals over the usable frequency range of the receiver and 98.7% of the injections when regions of dense radio frequency interference are excluded. In another pipeline that uses incoherent sums of 51 consecutive spectra, the recovery rate is ∼15 times smaller at ∼6%. The pipeline efficiency affects calculations of transmitter prevalence and SETI search volume. Accordingly, we developed an improved Drake figure of merit and a formalism to place upper limits on transmitter prevalence that take the pipeline efficiency and transmitter duty cycle into account. Based on our observations, we can state at the 95% confidence level that fewer than 6.6% of stars within 100 pc host a transmitter that is continuously transmitting a narrowband signal with an equivalent isotropic radiated power (EIRP) > 1013 W. For stars within 20,000 ly, the fraction of stars with detectable transmitters (EIRP > 5 × 1016 W) is at most 3 × 10−4. Finally, we showed that the UCLA SETI pipeline natively detects the signals detected with AI techniques by Ma et al.