Overview of radar detection methods for low altitude targets in marine environments

In this paper,a comprehensive overview of radar detection methods for low-altitude targets in maritime environments is presented,focusing on the challenges posed by sea clutter and multipath scattering.The performance of the radar detection methods under sea clutter,multipath,and combined conditions is categorized and summarized,and future research directions are outlined to enhance radar detection performance for low-altitude targets in maritime environments.

Beamspace maximum likelihood algorithm based on sum and difference beams for elevation estimation

Beamspace super-resolution methods for elevation estimation in multipath environment has attracted significant attention, especially the beamspace maximum likelihood(BML)algorithm. However, the difference beam is rarely used in superresolution methods, especially in low elevation estimation. The target airspace information in the difference beam is different from the target airspace information in the sum beam. And the use of difference beams does not significantly increase the complexity of the system and algorithms. Thus, this paper applies the difference beam to the beamformer to improve the elevation estimation performance of BML algorithm. And the direction and number of beams can be adjusted according to the actual needs. The theoretical target elevation angle root means square error(RMSE) and the computational complexity of the proposed algorithms are analyzed. Finally, computer simulations and real data processing results demonstrate the effectiveness of the proposed algorithms.

Mitigation of Optical Multipath Interference Algorithms in IM-DD Transmission System

This paper aimed to propose two algorithms,DA-M and RF-M,of reducing the impact of multipath interference(MPI)on intensity modulation direct detection(IM-DD)systems,particularly for four-level pulse amplitude modulation(PAM4)systems.DA-M reduced the fluctuation by averaging the signal in blocks,RF-M estimated MPI by subtracting the decision value of the corresponding block from the mean value of a signal block,and then generated interference-reduced samples by subtracting the interference signal from the product of the corresponding MPI estimate and then weighting factor.This paper firstly proposed to separate the signal before decision-making into multiple blocks,which significantly reduced the complexity of DA-M and RF-M.Simulation results showed that the MPI noise of 28 GBaud IMDD system under the linewidths of 1e5 Hz,1e6 Hz and 10e6 Hz can be effectively alleviated.

Improving Network Availability through Optimized Multipath Routing and Incremental Deployment Strategies

Currently,distributed routing protocols are constrained by offering a single path between any pair of nodes,thereby limiting the potential throughput and overall network performance.This approach not only restricts the flow of data but also makes the network susceptible to failures in case the primary path is disrupted.In contrast,routing protocols that leverage multiple paths within the network offer a more resilient and efficient solution.Multipath routing,as a fundamental concept,surpasses the limitations of traditional shortest path first protocols.It not only redirects traffic to unused resources,effectively mitigating network congestion,but also ensures load balancing across the network.This optimization significantly improves network utilization and boosts the overall performance,making it a widely recognized efficient method for enhancing network reliability.To further strengthen network resilience against failures,we introduce a routing scheme known as Multiple Nodes with at least Two Choices(MNTC).This innovative approach aims to significantly enhance network availability by providing each node with at least two routing choices.By doing so,it not only reduces the dependency on a single path but also creates redundant paths that can be utilized in case of failures,thereby enhancing the overall resilience of the network.To ensure the optimal placement of nodes,we propose three incremental deployment algorithms.These algorithms carefully select the most suitable set of nodes for deployment,taking into account various factors such as node connectivity,traffic patterns,and network topology.By deployingMNTCon a carefully chosen set of nodes,we can significantly enhance network reliability without the need for a complete overhaul of the existing infrastructure.We have conducted extensive evaluations of MNTC in diverse topological spaces,demonstrating its effectiveness in maintaining high network availability with minimal path stretch.The results are impressive,showing that even when implemented on just 60%of nodes,our incremental deployment method significantly boosts network availability.This underscores the potential of MNTC in enhancing network resilience and performance,making it a viable solution for modern networks facing increasing demands and complexities.The algorithms OSPF,TBFH,DC and LFC perform fast rerouting based on strict conditions,while MNTC is not restricted by these conditions.In five real network topologies,the average network availability ofMNTCis improved by 14.68%,6.28%,4.76%and 2.84%,respectively,compared with OSPF,TBFH,DC and LFC.

Passive IoT Localization Technology Based on SD-PDOA in NLOS and Multi-Path Environments

Addressing the challenges of passive Radio Frequency Identification(RFID)indoor localization technology in Non-Line-of-Sight(NLoS)and multipath environments,this paper presents an innovative approach by introducing a combined technology integrating an improved Kalman Filter with Space Domain Phase Difference of Arrival(SD-PDOA)and Received Signal Strength Indicator(RSSI).This methodology utilizes the distinct channel characteristics in multipath and NLoS contexts to effectively filter out interference and accurately extract localization information,thereby facilitating high precision and stability in passive RFID localization.The efficacy of this approach is demonstrated through detailed simulations and empirical tests conducted on a custom-built experimental platform consisting of passive RFID tags and an R420 reader.The findings are significant:in NLoS conditions,the four-antenna localization system achieved a notable localization accuracy of 0.25 m at a distance of 5 m.In complex multipath environments,this system achieved a localization accuracy of approximately 0.5 m at a distance of 5 m.When compared to conventional passive localization methods,our proposed solution exhibits a substantial improvement in indoor localization accuracy under NLoS and multipath conditions.This research provides a robust and effective technical solution for high-precision passive indoor localization in the Internet of Things(IoT)system,marking a significant advancement in the field.

Trust-based Intelligent Scheme for Mitigating Black Hole Attacks in IoT

Internet of Things(IoT)networks are characterized by a multitude of wireless,interconnected devices that can dynamically join or exit the network without centralized administration or fixed infrastructure for routing.While multipath routing in IoT networks can improve data transmission reliability and load balancing by establishing multiple paths between source and destination nodes,these networks are susceptible to security threats due to their wireless nature.Traditional security solutions developed for conventional networks are often ill-suited to the unique challenges posed by IoT environments.In response to these challenges,this paper proposes the integration of the Ad hoc On-demand Multipath Distance Vector(AOMDV)routing protocol with a trust model to enhance network performance.Key findings from this research demonstrate the successful fusion of AOMDV with a trust model,resulting in tangible improvements in network performance.The assessment of trustworthiness bolsters both security and routing capabilities in IoT networks.The trust model plays a crucial role in mitigating black hole attacks in IoT networks by evaluating the trustworthiness of nodes and helping in the identification and avoidance of malicious nodes that may act as black holes.Simulation results validate the efficacy of the proposed trust-based routing mechanism in achieving its objectives.Trust plays a pivotal role in decision-making and in the creation of secure distribution systems.By assessing the trustworthiness of nodes,both network security and routing efficiency can be enhanced.The effectiveness of the proposed trust-based routing mechanism is scrutinized through simulations,offering insights into its potential advantages in terms of improved network security and routing performance in the context of the IoT.

Adversarial Training-Aided Time-Varying Channel Prediction for TDD/FDD Systems

In this paper, a time-varying channel prediction method based on conditional generative adversarial network(CPcGAN) is proposed for time division duplexing/frequency division duplexing(TDD/FDD) systems. CPc GAN utilizes a discriminator to calculate the divergence between the predicted downlink channel state information(CSI) and the real sample distributions under a conditional constraint that is previous uplink CSI. The generator of CPcGAN learns the function relationship between the conditional constraint and the predicted downlink CSI and reduces the divergence between predicted CSI and real CSI.The capability of CPcGAN fitting data distribution can capture the time-varying and multipath characteristics of the channel well. Considering the propagation characteristics of real channel, we further develop a channel prediction error indicator to determine whether the generator reaches the best state. Simulations show that the CPcGAN can obtain higher prediction accuracy and lower system bit error rate than the existing methods under the same user speeds.

A Coverage Optimization Algorithm for Underwater Acoustic Sensor Networks based on Dijkstra Method

Dear Editor,This letter presents a coverage optimization algorithm for underwater acoustic sensor networks(UASN)based on Dijkstra method.Due to the particularity of underwater environment,the multipath effect and channel are easily disturbed,resulting in more node energy consumption.Once the energy is exhausted,the network transmission stability and network connectivity will be affected.

浅水声学通信中的多路径几何信道模型

Using the underwater acoustic channel(UWA)for information dissemination requires a high data rate.However,some phenomena like refraction,reflection,phase shift,and high attenuation are undesirably apparent when the subject of using UWA is raised.Accordingly,sound communication would be a highly challenging task to be accomplished.Therefore,proposing a model of acoustic underwater communication channels is critical because of the multipath interference originating from the surface and bottom of the ocean.In this contribution,a straightforward geometry channel model for vertical and horizontal marine communications is presented.To do so,transmission loss and channel impulse response are analyzed as a function of transmitter and receiver distance,water depth,and reflection rate.The results of the model proposed in this paper are in very good agreement with those available in the literature.Initial findings indicate that the delay spread of horizontal communication with a 1000 m range reaches79 ms and 0.3 s for 30 m vertical communication.

Physical-Layer Key Generation Based on Multipath Channel Diversity Using Dynamic Metasurface Antennas

Physical layer key generation(PKG)technology leverages the reciprocal channel randomness to generate the shared secret keys.The low secret key capacity of the existing PKG schemes is due to the reduction in degree-of-freedom from multipath fading channels to multipath combined channels.To improve the wireless key generation rate,we propose a multipath channel diversity-based PKG scheme.Assisted by dynamic metasurface antennas(DMA),a two-stage multipath channel parameter estimation algorithm is proposed to efficiently realize super-resolution multipath parameter estimation.The proposed algorithm first estimates the angle of arrival(AOA)based on the reconfigurable radiation pattern of DMA,and then utilizes the results to design the training beamforming and receive beamforming to improve the estimation accuracy of the path gain.After multipath separation and parameter estimation,multi-dimensional independent path gains are utilized for generating secret keys.Finally,we analyze the security and complexity of the proposed scheme and give an upper bound on the secret key capacity in the high signal-to-noise ratio(SNR)region.The simulation results demonstrate that the proposed scheme can greatly improve the secret key capacity compared with the existing schemes.

Non-LOS target localization via millimeter-wave automotive radar

This paper considers the non-line-of-sight(NLOS)vehicle localization problem by using millimeter-wave(MMW)automotive radar.Several preliminary attempts for NLOS vehicle detection are carried out and achieve good results.Firstly,an electromagnetic(EM)wave NLOS multipath propagation model for vehicle scene is established.Subsequently,with the help of available multipath echoes,a complete NLOS vehicle localiza-tion algorithm is proposed.Finally,simulation and experimental results validate the effectiveness of the established EM wave propagation model and the proposed NLOS vehicle localization algorithm.

Modeling GPS multipath effect based on spherical cap harmonic analysis

Most GPS positioning errors can be eliminated or removed by the differential technique or the modeling method,but the multipath effect is a special kind of system or gross error,so it is difficult to be simulated or eliminated.In order to improve the accuracy of GPS positioning,the single-epoch pseudorange multipath effects at GPS station were calculated,and firstly modeled based on the spherical cap harmonic（SCH）,which is the function of satellite longitude and latitude with the robust method.The accuracy of the kinematic point positioning technique was improved by correcting pseudorange observations with the multipath effect calculated by the SCH model,especially in the elevation direction.The spherical cap harmonic can be used to model the pseudorange multipath effect.

Hybrid particle filtering algorithm for GPS multipath mitigation

An altemative algorithm for mitigating GPS multipath was presented by integrating unscented Kalman filter （UKF） and wavelet transform with particle filter. Within consideration of particle degeneracy, UKF was taken for drawing particle. To remove the noise from raw data and data processing error, adaptive wavelet filtering with threshold was adopted while data preprocessing and drawing particle. Three algorithms, named EKF-PF, UKF-PF and WM-UKF-PF, were performed for comparison. The proposed WM-UKF-PF algorithm gives better error minimization, and significantly improves performance of multipath mitigation in terms of SNR and coefficient even though it has computation complexity. It is of significance for high-accuracy positioning and non-stationary deformation analysis.

基于Multipath的煤矿巷道三维模型构建方法

针对现有煤矿巷道三维模型存在灵活性和可移植性差、数据更新维护困难等问题,提出了一种基于Multipath的煤矿巷道三维模型构建方法。该方法通过定义点弧拓扑数据模型,将煤矿CAD格式数据转换为Geodatabase中的要素类,利用开发的ArcGIS Engine程序、通过插入节点坐标生成巷道三维模型,实现了煤矿巷道自动建模,有效减少了巷道三维建模的工作量。

An enhanced iterative joint channel estimation and symbol detection algorithm for OFDM systems

For orthogonal frequency division multiplexing (OFDM) wireless communication, the system throughput and data rate are usually limited by pilots, especially in a high mobility environment. In this paper, an enhanced iterative joint channel estimation and symbol detection algorithm is proposed to enhance the system throughput and data rate. With lower pilot power, the proposed scheme increases system throughput firstly, and then the channel estimation and symbol detection proceed iteratively within one OFDM symbol to improve the BER performance. In the proposed algorithm, the original channel estimate of each OFDM symbol is based on the channel estimate of the previous OFDM symbol, thus the variation of the mobile channel is traced efficiently, so the number of pilots in the time domain can be reduced greatly. Besides reducing the system overhead, the proposed algorithm is also shown by simulation to give much better BER performance than the conventional iterative algorithm does.

Multipath mitigation method for tracking Galileo signals

In order to improve the performance of multipath mitigation in tracking Galileo signals, a new multipath mitigation method named early-late strobe correlator （ELSC） is proposed. By applying the strobe correlator used widely in global positioning system （GPS） scenarios to Galileo E1 signals, it can be found that the strobe correlator has an undesirable level of performance when the delay of multipath signals is about 0. 5 chip. Combining several strobe correlators, the ELSC can effectively mitigate the multipath effect especially for the multipath signals with the 0. 5 chip delay. The multipath error envelopes between the strobe correlator and the ELSC are compared for Galileo E1 signals. The simulation results indicate that the ELSC performs excellently on multipath mitigation, and can be applied in both Galileo scenarios and GPS scenarios.

Performance analysis of space-time transmit diversity techniques for multi-antenna WCDMA systems

Several space-time coding based transmit diversity techniques for wideband code division multiple access (WCDMA) systems with four transmitter antennas are investigated. Performances of the rake receivers are analyzed and compared with those of the multi-antenna receive diversity techniques. Theoretical analysis shows that the multi-antenna transmit diversity techniques provide considerable performance gain at the mobile receiver in the wireless channel with less inherent multipath diversity, especially the G4 coding based scheme. Compared with the multi-antenna receive diversity techniques with the same diversity order, the transmit diversity techniques introduce much more multi-access plus multipath interference and require measures of interference suppression in the multi-user environments.

A comparison analysis of multipath extract methods in short-baseline applications of GPS

In order to eliminate the multipath errors existing in static short-baseline applications, a novel de-noising method based on a singular spectrum analysis （named as DSSA） is introduced to extract multipath signals. The multipath error is extracted from the double difference （DD） residuals by DSSA and then applied to the correct multipath error in subsequent measurements based on the correlation among adjacent epochs. Methods based on discrete wavelet transform （DWT） and stationary wavelet transform （SWT） are introduced as comparisons of DSSA based on analysis of a simulated signal. Real baseline residuals are tested to verify different extract methods. Results show that compared with the SWT, the DSSA improves the root mean square （RMS） of the residual by 48.6% and achieves a time reduction of 75.3%.

Unix服务器网口聚集技术的探讨

阐述了网口聚集技术的原理,结合对各种Unix服务器的实施,探讨了网口聚集技术的差异和共同点,以及对应用系统网络冗余性的重大作用。

HiQoS:An SDN-Based Multipath QoS Solution

Today's Internet architecture provides only "best effort" services,thus it cannot guarantee quality of service(QoS) for applications.Software Defined Network(SDN)is a new approach to computer networking that separates control plane and forwarding planes,and has the advantage of centralized control and programmability.In this paper,we propose HiQoS that provides QoS guarantees using SDN.Moreover,HiQoS makes use of multiple paths between source and destination and queuing mechanisms to guarantee QoS for different types of traffic.Experimental results show that our HiQoS scheme can reduce delay and increase throughput to guarantee QoS.Very importantly,HiQoS recovers from link failure very quickly by rerouting traffic from failed path to other available path.