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Copyright of Journal of Signal Processing is the property of Journal of Signal Processing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this work the discrete cosine transform is proposed for LTE systems with the aid of feed-forward neural network as a suitable equalizer to retrieve the effect of channel within Rayleigh Faded channels. This system was implemented using the QuadraturePhase Shift Keying as a modulation technique, and using different Maximum Doppler Shift, which represents the highest Doppler shift that can occur between the transmitter and the receiver in a given wireless channel. by using DCT-FFNN with different MDS values effectively mitigates signal distortion resulting from multipath propagation and common issues in wireless communication networks and demonstrates higher accuracy in predicting BER values. According to the research, the performance will be better at MDS 50 when compared to the rest of the MDS used in the paper. These advantages come with minimal loss in data rate and bandwidth and no additional expense in terms of power. The simulation results indicate that an FFNNs-based channel estimator outperforms the pilot-based channel estimator in LTE systems operating over a Rayleigh fading channel, because FFNNs have low complexity and can quickly and accurately adjust the signal strength of incoming signals based on their input. All LTE system models were implemented using MATLAB 2016. [ABSTRACT FROM AUTHOR]

One of the most important problems in traffic management is evaluating the amount of traffic and the velocity of vehicles passing through transportation ways and main streets. In this study, the traffic load is measured, and the speed of cars is estimated using the 24 GHz FMCW radar. In this process, an antenna is installed to record all the targets from the side of the highway. Next, the moving vehicles are classified according to their type, based on which the traffic load is provided to the user in each highway lane. Due to the radial velocity, low Doppler frequency, and variability with time, some challenges will emerge, for which two solutions will be provided. This paper describes the speed of cars and the amount of congestion in each highway lane presented by two new methods. Finally, with the process of canceling clutters observed by radar and detecting possible errors, a highway statistic is presented as a table. [ABSTRACT FROM AUTHOR]

This paper proposes a corner reflector and Luneburg ball reflector group. The omnidirectional radar cross-sectional (RCS) distribution characteristics of a fighter are simulated using the sharp and smooth RCS distribution features of the corner and the Luneburg ball reflectors, respectively. A new type of Doppler signal generation principle is proposed to design a Doppler frequency simulator to transmit frequency signals by connecting in parallel with the metal layer of the corner reflector and the Luneburg sphere ball, and then transmit through their other end. The existing radar target aircraft cannot simulate the RCS and speed of the targets that are less than 0.005 m2 by enhancing the echo intensity of the target location, which makes it impossible for the military to conduct practice drills and evaluate the effectiveness of the air defense systems. The experimental results show that the Doppler frequency simulator successfully simulates the target speed of 0-80 km/h and when the speed is greater than 20 km/h, the error of the simulation frequency is less than 1.5%. The proposed method can provide guidance and a theoretical basis for simulating the speed of various types of aircraft in future work.

Low Earth orbit (LEO) satellites have the potential to provide positioning, navigation and timing services in the future and are attracting widespread attention from researchers. However, due to rapid movements and a large number of LEO satellites, directly adopting the traditional code division multiple access (CDMA) method in the LEO mega-constellation navigation system will introduce a high computational complexity to the signal acquisition process of receivers and make the acquisition time much longer if receivers are in case of a cold start without assistance data. To decrease the acquisition complexity, we propose a new Doppler frequency code division multiple access (DFCDMA) method for LEO mega-constellation navigation systems. In this method, navigation signals broadcast by satellites in the same orbital plane are modulated with the same pseudorandom noise (PRN) code, while navigation signals broadcast by satellites in different orbital planes are modulated with distinct PRN codes. Through theoretical analysis and simulation, it is shown that satellites in the same orbital plane can achieve multiple access only by Doppler frequency at any position on the ground if the receiver velocity is less than 500 m/s. Therefore, low-speed receivers can distinguish LEO navigation signals by multiple combinations of different Doppler frequencies and PRN codes acquired. The results show that DFCDMA can achieve a fast acquisition and significantly shorten the acquisition time with similar acquisition sensitivity compared to CDMA in case of a cold start. Compared with the Doppler frequency code phase division multiple access (DFCP-DMA), DFCDMA has higher availability in the case of LEO mega-constellations and multipath environments. [ABSTRACT FROM AUTHOR]

This paper proposes a corner reflector and Luneburg ball reflector group. The omnidirectional radar cross-sectional (RCS) distribution characteristics of a fighter are simulated using the sharp and smooth RCS distribution features of the corner and the Luneburg ball reflectors, respectively. A new type of Doppler signal generation principle is proposed to design a Doppler frequency simulator to transmit frequency signals by connecting in parallel with the metal layer of the corner reflector and the Luneburg sphere ball, and then transmit through their other end. The existing radar target aircraft cannot simulate the RCS and speed of the targets that are less than 0.005 m² by enhancing the echo intensity of the target location, which makes it impossible for the military to conduct practice drills and evaluate the effectiveness of the air defense systems. The experimental results show that the Doppler frequency simulator successfully simulates the target speed of 0-80 km/h and when the speed is greater than 20 km/h, the error of the simulation frequency is less than 1.5%. The proposed method can provide guidance and a theoretical basis for simulating the speed of various types of aircraft in future work. [ABSTRACT FROM AUTHOR]

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Unmanned Aerial Vehicles (UAVs) are typical real-time embedded systems, which require precise locations for completing flight missions. The Global Navigation Satellite System (GNSS) plays a crucial role in navigation and positioning for UAVs. However, GNSS spoofing attacks pose an increasing threat to GNSS-dependent UAVs. Existing spoofing detection methods primarily rely on simulated data, perception data from multiple UAVs, or various control parameters. This paper proposes SigFeaDet, a signal feature-based GNSS spoofing detection approach for UAVs utilizing machine learning techniques. The core concept revolves around identifying anomalies in signal features arising from differences between authentic and spoofing signals. Key signal features, including Carrier-to-Noise Density Ratio (CN0) and Doppler frequency crucial for GNSS positioning, are employed to discern spoofing signals. Various machine learning algorithms are leveraged to train on GNSS signal data, determining the most effective classifier. TEXBAT GNSS dataset is processed to extract spoofing signal data, and flight experiments are conducted to gather GNSS data, augmenting the authentic GNSS signal dataset. The detection accuracy exceeds 95%. Equal Error Rate (EER) is approximately 5%. We evaluate various impact factors on SigFeaDet to show its robustness, including differences in velocities, altitudes, and experimental locations (10 kilometers apart), and the accuracy consistently surpasses 99%. [ABSTRACT FROM AUTHOR]

Noise reduction is one of the most important process used for signal processing in communication systems. The signal-to-noise ratio (SNR) is a key parameter to consider for minimizing the bit error rate (BER). The inherent noise found in millimeter-wave systems is mainly a combination of white noise and phase noise. Increasing the SNR in wireless data transfer systems can lead to reliability and performance improvements. To address this issue, we propose to use a recurrent neural network (RNN) with a long short-term memory (LSTM) autoencoder architecture to achieve signal noise reduction. This design is based on a composite LSTM autoencoder with a single encoder layer and two decoder layers. A V-band receiver test bench is designed and fabricated to provide a high-speed wireless communication system. Constellation diagrams display the output signals measured for various random sequences of PSK and QAM modulated signals. The LSTM autoencoder is trained in real time using various noisy signals. The trained system is then used to reduce noise levels in the tested signals. The SNR of the designed receiver is of the order of 11.8dB, and it increases to 13.66dB using the three-level LSTM autoencoder. Consequently, the proposed algorithm reduces the bit error rate from 10−8 to 10−11. The performance of the proposed algorithm is comparable to other noise reduction strategies. Augmented denoised signals are fed into a ResNet-152 deep convolutional network to perform the final classification. The demodulation types are classified with an accuracy of 99.93%. This is confirmed by experimental measurements.

Underwater acoustic (UWA) communication is the only option for underwater long-distance wireless communication. However, its data rate is very low, in tens of kbps, and the time-varying nature of the UWA channel exhibits a Doppler effect. The data rate can be increased using a multicarrier technique, such as Filter Bank Multicarrier (FBMC). The FBMC-OQAM system does not require a cyclic prefix (CP) to eliminate intersymbol interference (ISI). Therefore, compared to other multicarrier techniques, the FBMC-OQAM system achieves the maximum spectral efficiency. Despite the well-designed filter, synchronisation errors cause performance degradation in the FBMC-OQAM system. In this paper, we propose frame boundary and Doppler frequency estimation methods for the FBMC-OQAM system under UWA channels. In this study, we propose a preamble-based frame boundary. The conjugate symmetry property is used in the frame boundary estimation. The performance of the proposed technique was studied under different UWA channels with different Doppler scale. The proposed time synchronisation technique yielded multiple peaks under UWA channels. A method for identifying the peak that represents the frame boundary is proposed. We compared the performance of proposed timing metric with existing three reference timing metrics. The proposed timing metric exhibited superior over two metrics and almost identical performance with the Liming’s metric with less computational complexity. In addition, we propose a convolutional neural network (CNN)-based Doppler scale estimation method. The proposed technique was shown to estimate a wide range of Doppler scale factors. The performance of the proposed technique was studied by considering different UWA channels at different SNRs. The proposed CNN architecture is analysed by changing the CNN parameters. Stacked autoencoders were adopted for Doppler scale estimation and the performance of the proposed CNN-based Doppler scale estimation method was compared with the stacked autoencoders based Doppler scale estimation method. Simulation results show that the proposed CNN-based Doppler Scale estimator exhibits good performance in UWA channels at different SNRs and Doppler scale factors.

The aerodynamic thermal ionization affects the re-entry target, and the surface will form a 'plasma sheath (PSh).' The PSh with fluid characteristics will produce relative motion with the re-entry target. In the radar detection of the re-entry target, the relative motion characteristics cause the echo signal to couple different intra-pulse Doppler frequency components, forming a 'false target' on the one-dimensional range profile. In addition, the flight velocity of the re-entry target is exceptionally high (usually greater than 10 Mach), and there will be a severe phenomenon of migration through range cells (MTRC) during the detection period, which will make the coherent integration of the multi-period radar echo signal invalid and further affect the reliable detection of the re-entry target. Aiming at the 'false target phenomenon' and MTRC phenomenon in the process of re-entry target detection, this paper proposes an improved keystone algorithm. Based on the traditional keystone algorithm, a reliable, coherent integration method for radar echo of the plasma-sheath-covered target is proposed by modifying the scale transformation factor and constructing the Doppler frequency compensation function. It can effectively compensate the intra-pulse Doppler frequency and inter-pulse Doppler frequency to improve the energy gain of the real target and lay a theoretical foundation for the reliable detection of the plasma-sheath-covered target. [ABSTRACT FROM AUTHOR]

This paper proposes a full-rate space-time code selection technique for multiple transmitter antenna diversity systems. The technique uses orthogonal space-time codes for transmitting with two antennas and a quasi-orthogonal space-time code when transmitting with four antennas. We selected the space-time code and the transmitter antennas by comparing the equivalent SISO channels with a set of predetermined threshold levels, found off-line as a function of the Doppler frequency. The performance of the proposed technique was evaluated using the error rate and the spectral efficiency, outperforming other existing techniques. [ABSTRACT FROM AUTHOR]

It is an important development direction to take advantage of low-earth-orbit (LEO) satellites by establishing a LEO satellite navigation system as a supplement to Global Navigation Satellite Systems in the future. On account of the fast motion of LEO satellites, there is a significant and fast change in the Doppler frequency of LEO navigation signals. Since a LEO navigation system usually consists of a large number of satellites, the search range of carrier frequencies and satellite numbers is correspondingly large in the signal acquisition process. Adopting the traditional code division multiple access (CDMA) technique will bring extremely high computational complexity to the acquisition process of LEO navigation signals, which leads to a much longer acquisition time. Considering the characteristics of LEO navigation signals, we proposed a Doppler Frequency-Code Phase Division Multiple Access (DFCP-DMA) technique in order to achieve a fast acquisition of LEO navigation signals. Because the motion of LEO satellites is fast, Doppler frequencies and code phases of LEO navigation signals arriving at the receiver differ significantly. Thus, receivers can distinguish LEO navigation signals by multiple combinations of different Doppler frequencies and code phases acquired. To decrease the acquisition complexity, all LEO satellites broadcast spread-spectrum navigation signals modulated by the same spreading code in DFCP-DMA, and receivers can acquire all navigation signals using only this spreading code. Theoretical analysis and simulation results show that, compared with CDMA, DFCP-DMA can significantly reduce the acquisition complexity without any loss in the acquisition sensitivity, which can shorten the acquisition time to 1/M, where M is the number of satellites. There is a high application prospect for DFCP-DMA in future LEO navigation systems. [ABSTRACT FROM AUTHOR]

Values for Doppler center frequency are calculated from the echo signal at the satellite using the Doppler centroid method and so include the predicted Doppler frequency caused by the relative motion of the satellite and the Earth, which is the main component of Doppler center frequency and must be removed to obtain the Doppler frequency anomaly for ocean current measurement. In this paper, a new Doppler frequency anomaly algorithm was proposed when measuring surface currents with synthetic aperture radar (SAR). The key of the proposed algorithm involved mean filtering method in the range direction and linear fitting in the azimuth direction to remove the radial and the azimuthal component of predicted Doppler frequency from the Doppler center frequency, respectively. The basis is that the theoretical Doppler center frequency model of SAR exhibits an approximately linear characteristic in both the range direction and in the azimuth direction. With the help of the new algorithm for predicted Doppler frequency removal, the estimation error of Doppler frequency anomaly can be reduced by avoiding employing the theoretical antenna pattern and imperfect satellite attitude parameters in the conventional Doppler frequency method. SAR measurement results demonstrated that, compared to the conventional Doppler frequency with/without error correction method, the proposed algorithm allows for a pronounced improvement in the current measuring accuracy in comparison with the global ocean multi-observation (MOB) products. In addition, the effectiveness and robustness of the proposed Doppler algorithm has been demonstrated by its application in the high velocity current in the Kuroshio region. [ABSTRACT FROM AUTHOR]

Human movement detection based on millimeter-wave radar sensors is a technology of interest in various areas such as for smart surveillance, security, behavioral biometrics, biomedical systems, robotics, etc. This paper shows the feasibility and effectiveness of using a compact 24 GHz Doppler radar with a built-in low-noise microwave amplifier (LNA) for detecting and extracting signals coming from human motion. Reliability and accuracy is assessed based on a comprehensive theoretical analysis, and on simulation results followed by experimental investigations. A continuous wavelet transform (CWT) is used to decompose in-phase and quadrature (${I/Q}$) baseband signals to extract information about the dynamics of the system. The dataset consists of 1000 recordings in 8 motion classes (standing, walking, sitting, etc.). We propose to apply a two-channel convolutional neural network (CNN), which is composed of two CNN channels, for learning high-level features from time-domain signals and CWT spectrograms. One channel has four one-dimensional (1D) convolutional and pooling layers, and the other channel is made of three two-dimensional (2D) convolutional and pooling layers. In addition, the ${I/Q}$ signals are denoised by using Savitzky-Golay filtering, and both noisy and denoised signals are used as input signals for deep learning data augmentation purpose. We achieved an overall classification accuracy rate of 98.85% in motion classification for a two-branch CNN architecture, and an accuracy rate of 95.3% for a one-branch 2D-CNN. Our results show that a dual-channel CNN model can greatly increase the classification capabilities of human motion recognition and classification, and the proposed method can be effectively used with various radar signal classifications. [ABSTRACT FROM AUTHOR]

GNSS (Global Navigation Satellite System) spoofing has become a great threat in recent years because of its elusiveness and harmfulness. For anti-spoofing usages, utilization of additional independent sensors is a preferred choice. In this work we develop a MEMS (Micro-Electro-Mechanical-Systems) IMU (Inertial Measurement Unit) based spoofing detection and exclusion method by first analyzing the relationship between the Doppler frequency from each navigation signal and the output from the IMU and then evaluating the residual. The detector is a steady-state spoofing detector which can provide continual anti-spoofing result throughout the spoofing attack, as it only requires raw measurements from the two sensors and a rather rough prior knowledge of the position of the host. Simulations are conducted to verify the theoretical derivation and to evaluate the anti-spoofing performance of the proposed method. Field experiments are carried out and the experiment results are analyzed, in which the proposed steady-state detector exhibits improved ability of spoofing identification over traditional methods under continuous spoofing attacks, by clearly distinguishing the authentic navigation signals from the counterfeited ones. Moreover, both the simulation and the field experiment demonstrate that a prior knowledge of the position of the host with the uncertainty of hundreds of kilometers, which can be readily obtained from various methods, is acceptable for the proposed detector. [ABSTRACT FROM AUTHOR]

The plasma sheath will be generated on the surface of the reentry object due to the effect of aerodynamic thermoionization, causing multicomponent signals with Doppler frequency components in the radar echo. This situation will further result in the appearance of false targets that seriously affect the detection of reentry targets by radar, causing positioning errors and even tracking losses. In this article, the echo signal model of the plasma sheath covered reentry target is established, and the multidomain characteristics of the echo signal in terms of time, time-frequency, and range are analyzed, revealing the influence mechanism of plasma sheath on radar detection of reentry target. Through range-period analysis, the influence of intrapulse Doppler frequency caused by plasma sheath is determined as well as the interpulse Doppler frequency on target range measurement. Theoretical analyses conducted in this study are verified by simulation results, laying theoretical foundation for effective detection and reliable tracking of plasma sheath covered reentry targets. [ABSTRACT FROM AUTHOR]

Ocean currents are a key element in ocean processes and in meteorology, affecting material transport and modulating climate change patterns. The Doppler frequency shift information of the synthetic aperture radar (SAR) echo signal can reflect the dynamic characteristics of the sea surface, and has become an essential sea surface dynamic remote sensing parameter. Studies have verified that the instantaneous Doppler frequency shift can realize the SAR detection of the sea surface current. However, the validation of SAR-derived ocean current data and a thorough analysis of the errors associated with them remain lacking. In this study, we derive high spatial resolution flow measurements for the Kuroshio in the East China Sea from SAR data using a theoretical model of shifts in Doppler frequency driven by ocean surface current. Global ocean multi observation (MOB) products and global surface Lagrangian drifter (GLD) data are used to validate the Kuroshio flow retrieved from the SAR data. Results show that the central flow velocity for the Kuroshio derived from the SAR is 0.4–1.5 m/s. The error distribution between SAR ocean currents and MOB products is an approximate standard normal distribution, with the 90% confidence interval concentrated between −0.1 m/s and 0.1 m/s. Comparative analysis of SAR ocean current and GLD products, the correlation coefficient is 0.803, which shows to be significant at a confidence level of 99%. The cross-validation of different ocean current dataset illustrate that the SAR radial current captures the positions and dynamics of the Kuroshio central flow and the Kuroshio Counter Current, and has the capability to monitor current velocity over a wide range of values. [ABSTRACT FROM AUTHOR]

A simple and all-optical Doppler frequency shift (DFS) measurement system is presented. It is based on a dual-drive Mach Zehnder modulator (DDMZM) driven by a transmitted signal and an echo signal received by an antenna. A low-frequency sawtooth wave is applied to the DDMZM DC port to frequency shift the carrier and sidebands generated by the transmitted signal. Beating of a frequency-shifted transmitted signal sideband and an echo signal sideband at the photodetector produces a low-frequency electrical signal. The DFS, and consequently the speed and moving direction of a target, can be obtained from the frequency of this low-frequency electrical signal. The DDMZM used in the proposed DFS measurement system does not need to be operated at a specific point in the transfer function and hence it has no bias drift problem. The proposed DFS measurement technique can be used in both CW and pulsed radar systems. Experimental results demonstrate the proposed DFS measurement system has a wide operating frequency range of 10 GHz to 19.95 GHz, small DFS measurement error of less than ±0.6 Hz and long-term stable performance. Results also demonstrate, for the first time, DFS measurement of a pulsed signal using a microwave photonic technique. [ABSTRACT FROM AUTHOR]

Message passing (MP) aided detectors are designed for orthogonal time frequency space (OTFS) modulated system. We first characterize the transmit-receive relationship of our OTFS-modulated system in the delay-Doppler (DD) domain by designing a joint factor graph. Based on this joint factor graph, we then conceive a joint message passing aided (JMPA) detector. Furthermore, a novel low-complexity Gaussian approximate MP (GA-MP) detector is also conceived, which models the a posteriori probabilities propagated through the proposed joint factor graph by Gaussian distributions. Finally, we demonstrate that the proposed GA-MP detector outperforms the state-of-the-art MP detector by at least 1.5 dB at a bit error ratio (BER) of $10^{-4}$ , while keeping the same complexity order. [ABSTRACT FROM AUTHOR]

The aerodynamic thermal ionization affects the re-entry target, and the surface will form a ‘plasma sheath (PSh).’ The PSh with fluid characteristics will produce relative motion with the re-entry target. In the radar detection of the re-entry target, the relative motion characteristics cause the echo signal to couple different intra-pulse Doppler frequency components, forming a ‘false target’ on the one-dimensional range profile. In addition, the flight velocity of the re-entry target is exceptionally high (usually greater than 10 Mach), and there will be a severe phenomenon of migration through range cells (MTRC) during the detection period, which will make the coherent integration of the multi-period radar echo signal invalid and further affect the reliable detection of the re-entry target. Aiming at the ‘false target phenomenon’ and MTRC phenomenon in the process of re-entry target detection, this paper proposes an improved keystone algorithm. Based on the traditional keystone algorithm, a reliable, coherent integration method for radar echo of the plasma-sheath-covered target is proposed by modifying the scale transformation factor and constructing the Doppler frequency compensation function. It can effectively compensate the intra-pulse Doppler frequency and inter-pulse Doppler frequency to improve the energy gain of the real target and lay a theoretical foundation for the reliable detection of the plasma-sheath-covered target.

Along with the rapid development of marine radar, and particularly those carried on aircraft, the detection of small-sized targets which pose an increasing threat has become one of the main areas of interest. However, by considering an observation chain from an aircraft (such as a drone) in a maritime environment, with the aim of detecting and tracking of low signal-to-clutter ratio (SCR) targets, one of the important points would be the analysis of the radar system performance according to the radar input parameters, the atmospheric propagation medium, the various sea clutter characterization, and the type of targets (RCS, speed, etc.) in this environment. Therefore, it is necessary to obtain the overall path loss including the anomalous atmospheric environment, gas attenuation, clouds attenuation, rainfall attenuation, and beam scanning loss. To consider atmospheric attenuations, ITU-R models are used. On another side, because of spikes and dynamic variation properties, sea clutter is generally described by the statistical distribution with long tail and by its wider Doppler spectrum. Conventional algorithms such as those based on statistical models, MTI, and MTD processing are often limited, especially for the target of low speed and low RCS. Therefore, sea clutter, including empirical and statistical models available, is considered to estimate and simulate the impact of radar input parameters, targets RCS, and sea state on detection performance. The Doppler frequency of target echo which can be exploited for coherent processing is described by assuming an adequate scenario of observation geometry.

Global navigation satellite system reflectometry technology (GNSS-R) is rarely used for river flow velocity inversion, and in particular, there is currently no research using the BeiDou Navigation Satellite System reflectometry technology (BDS-R) for river flow velocity inversion. In this paper, a carrier phase observation of river flow velocity inversion model is proposed. The interference phase is the integral of the Doppler frequency. The raw intermediate frequency (IF) data sets are processed through an open-loop method to obtain the Doppler frequency observation generated by river flow and then realize velocity inversion. The shore-based river current measurement was conducted on the south bank of Dashengguan Yangtze River in Nanjing city, Jiangsu Province, for nearly two hours on 22 April 2021. After realizing the inversion of river flow velocity in GPS L1, the combined inversion of BDS B1I GEO satellite and IGSO satellite is realized for the first time, which demonstrates the feasibility of river flow velocity inversion using BDS reflected signals. Compared with the real river flow velocity, the GPS L1 PRN 4 (1st period) inversion precision reaches up to 0.028 m/s (mean absolute error, MAE) and 0.036 m/s (root mean square error, RMSE). In parallel, BDS GEO 2 inversion precision can reach 0.048 m/s (MAE) and 0.063 m/s (RMSE), and BDS IGSO 10 inversion precision is 0.061 m/s (MAE) and 0.073 m/s (RMSE). These results illustrate that satellite elevation change rate and distance between specular points and current meter may have a negative effect on the accuracy of river flow velocity inversion. Specular points obstructed by obstacles or too far from the velocity meter may introduce uncertain error in both MAE and RMSE. Neither the satellite elevation nor the signal strength has an obvious correlation with inversion precision, which is consistent with the theoretical principle.

Global navigation satellite system reflectometry technology (GNSS-R) is rarely used for river flow velocity inversion, and in particular, there is currently no research using the BeiDou Navigation Satellite System reflectometry technology (BDS-R) for river flow velocity inversion. In this paper, a carrier phase observation of river flow velocity inversion model is proposed. The interference phase is the integral of the Doppler frequency. The raw intermediate frequency (IF) data sets are processed through an open-loop method to obtain the Doppler frequency observation generated by river flow and then realize velocity inversion. The shore-based river current measurement was conducted on the south bank of Dashengguan Yangtze River in Nanjing city, Jiangsu Province, for nearly two hours on 22 April 2021. After realizing the inversion of river flow velocity in GPS L1, the combined inversion of BDS B1I GEO satellite and IGSO satellite is realized for the first time, which demonstrates the feasibility of river flow velocity inversion using BDS reflected signals. Compared with the real river flow velocity, the GPS L1 PRN 4 (1st period) inversion precision reaches up to 0.028 m/s (mean absolute error, MAE) and 0.036 m/s (root mean square error, RMSE). In parallel, BDS GEO 2 inversion precision can reach 0.048 m/s (MAE) and 0.063 m/s (RMSE), and BDS IGSO 10 inversion precision is 0.061 m/s (MAE) and 0.073 m/s (RMSE). These results illustrate that satellite elevation change rate and distance between specular points and current meter may have a negative effect on the accuracy of river flow velocity inversion. Specular points obstructed by obstacles or too far from the velocity meter may introduce uncertain error in both MAE and RMSE. Neither the satellite elevation nor the signal strength has an obvious correlation with inversion precision, which is consistent with the theoretical principle. [ABSTRACT FROM AUTHOR]

Along with the rapid development of marine radar, and particularly those carried on aircraft, the detection of small-sized targets which pose an increasing threat has become one of the main areas of interest. However, by considering an observation chain from an aircraft (such as a drone) in a maritime environment, with the aim of detecting and tracking of low signal-to-clutter ratio (SCR) targets, one of the important points would be the analysis of the radar system performance according to the radar input parameters, the atmospheric propagation medium, the various sea clutter characterization, and the type of targets (RCS, speed, etc.) in this environment. Therefore, it is necessary to obtain the overall path loss including the anomalous atmospheric environment, gas attenuation, clouds attenuation, rainfall attenuation, and beam scanning loss. To consider atmospheric attenuations, ITU-R models are used. On another side, because of spikes and dynamic variation properties, sea clutter is generally described by the statistical distribution with long tail and by its wider Doppler spectrum. Conventional algorithms such as those based on statistical models, MTI, and MTD processing are often limited, especially for the target of low speed and low RCS. Therefore, sea clutter, including empirical and statistical models available, is considered to estimate and simulate the impact of radar input parameters, targets RCS, and sea state on detection performance. The Doppler frequency of target echo which can be exploited for coherent processing is described by assuming an adequate scenario of observation geometry.