Accuracy improvement of GPS/MEMS-INS integrated navigation system during GPS signal outage for land vehicle navigation

To improve the reliability and accuracy of the global po- sitioning system （GPS）/micro electromechanical system （MEMS）- inertial navigation system （INS） integrated navigation system, this paper proposes two different methods. Based on wavelet threshold denoising and functional coefficient autoregressive （FAR） model- ing, a combined data processing method is presented for MEMS inertial sensor, and GPS attitude information is also introduced to improve the estimation accuracy of MEMS inertial sensor errors. Then the positioning accuracy during GPS signal short outage is enhanced. To improve the positioning accuracy when a GPS signal is blocked for long time and solve the problem of the tra- ditional adaptive neuro-fuzzy inference system （ANFIS） method with poor dynamic adaptation and large calculation amount, a self-constructive ANFIS （SCANFIS） combined with the extended Kalman filter （EKF） is proposed for MEMS-INS errors modeling and predicting. Experimental road test results validate the effi- ciency of the proposed methods.

Angular glint calculation and analysis of radar targets via adaptive cross approximation algorithm

Angular glint is a significant electromagnetic （EM） scattering signature of extended radar targets. Based on the adaptive cross approximation （ACA） algorithm accelerated method of moments （MoM） and the plane incident wave assumption, the narrowband, wideband and newly developed high-resolution range profile （HRRP） based angular glint calculation formulations are derived and applied to arbitrarily shaped three-dimensional （3D） perfectly electrical y conducting （PEC） objects. In addition, the near-field angular glint is emphasized, which is of great importance for radarseeker applications. Furthermore, with the HRRP based angular glint, an approach to rigorously determine range resolution cel s which own relatively smal er angular glint is provided. Numerical results are presented with new findings to demonstrate the usefulness of the developed formulations.

Determination of Total Electron Content at Equatorial Region—Thailand Using Radio Occultation Technique

This paper investigates the total electron content (TEC) which is a major challenge to space and related industries, most especially in an equatorial region like Thailand within the geographical latitude 07°35'N - 20°17'N. This research was achieved using radio occultation data from COSMIC mission. The monthly, seasonal and annual TEC and electron density variation monitoring conducted during increasing solar activity from 2010 to 2013 due to changes and instability of ionospheric parameters. It was observed that electron density and TEC was predominant in summer season. Summer has the highest electron density and TEC values all through and the annual mean values keep on increasing within the period under consideration. In conclusion, ionospheric fluctuations and perturbations were observed to be at pick between the months of March and May. The results of the study demonstrated that ionospheric irregularities were steadily on the increase, confirming 24th solar cycle prediction by NASA and depended on many factors among the major ones which are located on the latitude, season and solar activity.

Coherent change detection of fine traces based on multi-angle SAR observations

Coherent change detection(CCD) is an effective method to detect subtle scene changes that occur between temporal synthetic aperture radar(SAR) observations. Most coherence estimators are obtained from a Hermitian product based on local statistics. Increasing the number of samples in the local window can improve the estimation bias, but cause the loss of the estimated images spatial resolution. The limitations of these estimators lead to unclear contour of the disturbed region, and even the omission of fine change targets. In this paper, a CCD approach is proposed to detect fine scene changes from multi-temporal and multi-angle SAR image pairs. Multi-angle CCD estimator can improve the contrast between the change target and the background clutter by jointly accumulating singleangle alternative estimator results without further loss of image resolution. The sensitivity of detection performance to image quantity and angle interval is analyzed. Theoretical analysis and experimental results verify the performance of the proposed algorithm.

Average Capacity of OAM-Multiplexed FSO System with Vortex Beam Propagating Through Non-Kolmogorov Turbulence

The propagation of vortex beam in atmospheric turbulence is of significant importance in theoretical study and practical applications. Based on extended Huygens-Fresnel integral and the Rytov approximation, the average capacity of orbital angular momentum(OAM)-multiplexed Laguerre-Gaussian(LG) beam propagating through non-Kolmogorov turbulence is presented, and the analytical expression of spiral spectrum of LG beam has been deduced. The average capacity of FSO system is numerically calculated and the influence of exponent parameter, transmission height, structure constant, wavelength, outer scale and inner scale on average capacity are also analyzed in detail. Outcomes show that smaller structure constant, outer scale, higher transmission height and larger wavelength, inner scale are conducive to improve average capacity in different extent. Results acquires in this paper have potential application value in optical communication within non-Kolmogorov turbulence.

Fast image super-resolution algorithm based on multi-resolution dictionary learning and sparse representation

Sparse representation has attracted extensive attention and performed well on image super-resolution（SR） in the last decade. However, many current image SR methods face the contradiction of detail recovery and artifact suppression. We propose a multi-resolution dictionary learning（MRDL） model to solve this contradiction, and give a fast single image SR method based on the MRDL model. To obtain the MRDL model, we first extract multi-scale patches by using our proposed adaptive patch partition method（APPM）. The APPM divides images into patches of different sizes according to their detail richness. Then, the multiresolution dictionary pairs, which contain structural primitives of various resolutions, can be trained from these multi-scale patches.Owing to the MRDL strategy, our SR algorithm not only recovers details well, with less jag and noise, but also significantly improves the computational efficiency. Experimental results validate that our algorithm performs better than other SR methods in evaluation metrics and visual perception.

SER analysis and power allocation for hybrid cooperative transmission system

The symbol-error-rate（SER） and power allocation for hybrid cooperative（HC） transmission system are investigated.Closed-form SER expression is derived by using the moment generating function（MGF）-based approach.However,the resultant SER contains an MGF of the harmonic mean of two independent random variables（RVs）,which is not tractable in SER analysis.We present a simple MGF expression of the harmonic mean of two independent RVs which avoids the hypergeometric functions used commonly in previous studies.Using the simple MGF,closed-form SER for HC system with M-ary phase shift keying（M-PSK） signals is provided.Further,an approximation as well as an upper bound of the SER is presented.It is shown that the SER approximation is asymptotically tight.Based on the tight SER approximation,the power allocation of the HC system is investigated.It is shown that the optimal power allocation does not depend on the fading parameters of the source-destination（SD） channel and it only depends on the source-relay（SR） and relay-destination（RD） channels.Moreover,the performance gain of the power allocation depends on the ratio of the channel quality between RD and SR.With the increase of this ratio,more performance gain can be acquired.

Adaptive Maxwell’s Equations Derived Optimization and Its Application in Antenna Array Synthesis

In this paper,a self-adaptive method for the Maxwell’s Equations Derived Optimization(MEDO)is proposed.It is implemented by applying the Sequential Model-Based Optimization(SMBO)algorithm to the iterations of the MEDO,and achieves the automatic adjustment of the parameters.The proposed method is named as adaptive Maxwell’s equations derived optimization(AMEDO).In order to evaluate the performance of AMEDO,eight benchmarks are used and the results are compared with the original MEDO method.The results show that AMEDO can greatly reduce the workload of manual adjustment of parameters,and at the same time can keep the accuracy and stability.Moreover,the convergence of the optimization can be accelerated due to the dynamical adjustment of the parameters.In the end,the proposed AMEDO is applied to the side lobe level suppression and array failure correction of a linear antenna array,and shows great potential in antenna array synthesis.

CROSS-RANGE RESOLUTION OF SYNTHETIC APERTURE RADAR BASED ON DIVING MODEL

This paper concentrates on the cross-range resolution of Synthetic Aperture Radar(SAR) based on diving model.In comparison to the azimuth resolution,the cross-range resolution can manifest the two-dimensional resolution ability of the imaging sensor SAR correctly.The diving model of SAR is an extended model from the conventional stripmap model,and the cross-range resolution expression is deduced from the equivalent linear frequency modulation pulses' compression.This expression points out that only the cross-range velocity component of the horizontal velocity contributes to the cross-range resolution.Also the cross-range resolution expressions and the performance of the conventional stripmap operation,squint side-look operation and beam circular-scanning operation are discussed.The cross-range resolution expression based on diving model will provide more general and more accurate reference.

Re-scaling and adaptive stochastic resonance as a tool for weak GNSS signal acquisition

Weak global navigation satellite system（GNSS） signal acquisition has been a limitation for high sensitivity GPS receivers. This paper modifies the traditional acquisition algorithms and proposes a new weak GNSS signal acquisition method using re-scaling and adaptive stochastic resonance（SR）. The adoption of classical SR is limited to low-frequency and periodic signals. Given that GNSS signal frequency is high and that the periodic feature of the GNSS signal is affected by the Doppler frequency shift, classical SR methods cannot be directly used to acquire GNSS signals. Therefore, the re-scaling technique is used in our study to expand its usage to high-frequency signals and adaptive control technique is used to gradually determine the Doppler shift effect in GNSS signal buried in strong noises. The effectiveness of our proposed method was verified by the simulations on GPS L1 signals. The simulation results indicate that the new algorithm based on SR can reach-181 d BW sensitivity with a very short data length of 1 ms.

FREQUENCY-TIME BLOCK CODE FOR FREQUENCY DIVERSITY IN UWB-OFDM SYSTEMS

The Ultra-WideBand Orthogonal Frequency Division Multiplexing (UWB-OFDM) approach is a promising physical-layer technique for short-range, high data-rate wireless networks. As the occupied band-width increases, however, its implementation becomes more and more difficult. In order to make it easier to achieve a UWB-OFDM system, a complexity-reduced Frequency diversity (F-diversity) scheme, Fre-quency-Time Block Code (FTBC), is presented in this paper. The FTBC halves the sampling rate required by other F-diversity techniques so as to cut down the cost of UWB-OFDM systems with F-diversity to a certain extent.

Coded Multicasting for Content Delivery over Predictable Time-Varying Satellite Communication Networks

With the development of astronautic technology, communication satellites now have a tremendous gain in both quantity and quality, and have already shown their capability on multi-functional converged communication other than telecommunication. Under this circumstance, increasing the transmission efficiency of satellite communication network becomes a top priority. In this paper, we focus on content delivery service on satellite networks, where each ground station may have prefetched some file fragments. We cast this problem into a coded caching framework so as to exploit the coded multicast gain for minimizing the satellite communication load. We first propose an optimization-based coded multicast scheme by considering the special property that the satellite network topology is predictable and timevariant. Then, a greedy based fast algorithm is proposed, which can tremendously reduce the computation complexity with a small loss in optimality. Simulation experiments conducted on two Walker constellation satellite networks show that our proposed coded multicast method can efficiently reduce the communication load of satellite networks.

A novel Bayesian-based INS/GNSS integrated positioning method with both adaptability and robustness in urban environments

Achieving higher accuracy positioning results in urban environments at a lower cost has been an important pursuit in areas such as autonomous driving and intelligent transportation.Lowcost Inertial Navigation System and Global Navigation Satellite System(INS/GNSS)integrated navigation systems have been an important means of fulfilling the above quest due to the complementary error characteristics between INS and GNSS.The complex urban driving environment requires the system sufficiently adaptive to keep up with the time-varying measurement noise and sufficiently robust to cope with measurement outliers and prior uncertainties.However,many efforts lack a balance between adaptability and robustness.In this paper,a novel positioning method with both adaptability and robustness is proposed by coupling the Mahalanobis distance method,the Variational Bayesian method and the student’s t-distribution in one process(M-VBt method).This method is robust against non-Gaussian noise and priori uncertainties,plus adaptive against measurement noise uncertainty and time-varying noise.The field test results show that the M-VBt method(especially the Mahalanobis distance part)has significantly improved the system performance in the complex urban driving environment.

A whole-net cooperative positioning method based on CDGNSS and inter-vehicle ranging

Relative positioning is recognized as an important issue for vehicles in urban environments.Multi-vehicle Cooperative Positioning(CP)techniques which fuse the Global Navigation Satellite System(GNSS)and inter-vehicle ranging have attracted attention in improving the performance of baseline estimation between vehicles.However,current CP methods estimate the baselines separately and ignore the interactions among the positioning information of different baselines.These interactions are called’information coupling’.In this work,we propose a new multivehicle precise CP framework using the coupled information in the network based on the Carrier Differential GNSS(CDGNSS)and inter-vehicle ranging.We demonstrate the benefit of the coupled information by deriving the Cramer-Rao Lower Bound(CRLB)of the float estimation in CP.To fully use this coupled information,we propose a Whole-Net CP(WN-CP)method which consists of the Whole-Net Extended Kalman Filter(WN-EKF)as the float estimation filter,and the Partial Baseline Fixing(PBF)as the ambiguity resolution part.The WN-EKF fuses the measurements of all baselines simultaneously to improve the performance of float estimation,and the PBF strategy fixes the ambiguities of the one baseline to be estimated,instead of full ambiguity resolution,to reduce the computation load of ambiguity resolution.Field tests involving four vehicles were conducted in urban environments.The results show that the proposed WN-CP method can achieve better performance and meanwhile maintain a low computation load compared to the existing methods.

All-optical suppression on the impact of Sun outage in laser satellite communication systems by using a nonlinear semiconductor optical amplifier

We introduce an all-optical approach,optical parametric amplification(OPA)processor to suppress the impact of Sun outage in laser satellite communication systems,which is implemented by only one nonlinear semiconductor optical amplifier driven by both electrical and optical pumps.The optimized OPA processor,with a current of 539 mA and a pump-to-signal ratio of 16 dB,could significantly improve the signal quality by 3.5 dB in experiments for the elevation angle of Sun radiation of 0 rad.The signal quality improvement is observed in the whole range of the elevation angle,confirming the effectiveness of the proposed OPA processor in the field of Sun radiation mitigation.

Remote sensing and its applications using GNSS reflected signals:advances and prospects

The Global Navigation Satellite Systems(GNSS),including the US’s GPS,China’s BDS,the European Union’s Galileo,and Russia’s GLONASS,offer real-time,all-weather,any-time,anywhere and high precision observations by transmitting L band signals continuously,which have been widely used for positioning,navigation and timing.With the development of GNSS technology,it has been found that GNSS-reflected signals can be used to detect Earth’s surface characteristics together with other signals of opportunity.In this paper,the current status and latest advances are presented on Global Navigation Satellite System-Reflectometry(GNSS-R)in theory,methods,techniques and observations.New developments and progresses in GNSS-R instruments,theoretical modeling,and signal processing,ground and space-/air-borne experiments,parameters retrieval(e.g.wind speed,sea surface height,soil moisture,ice thickness),sea surface altimetry and applications in the atmosphere,oceans,land,vegetation,and cryosphere are given and reviewed in details.Meanwhile,the challenges in the GNSS-R development of each field are also given.Finally,the future applications and prospects of GNSS-R are discussed,including multi-GNSS reflectometry,new GNSS-R receivers,GNSS-R missions,and emerging applications,such as mesoscale ocean eddies,ocean phytoplankton blooms,microplastics detection,target recognition,river flow,desert studies,natural hazards and landslides monitoring.

Integration of GPS and low cost INS for pedestrian navigation aided by building layout

In outdoor environments, GPS is often used for pedestrian navigation by utilizing its signals for position computation, but in indoor or semi-obstructed environments, GPS signals are often unavailable. Therefore, pedestrian navigation for these environments should be realized by the integration of GPS and inertial navigation system （INS）. However, the lowcost INS could induce errors that may result in a large position drift. The problem can be minimized by mounting the sensors on the pedestrian＇s foot, using zero velocity update （ZUPT） method with the standard navigation algorithm to restrict the error growth. However, heading drift still remains despite using ZUPT measurements since the heading error is unobservable. Also, tbot mounted INS suffers from the initialization ambiguity of position and heading from GPS. In this paper, a novel algorithm is developed to mitigate the heading drift problem when using ZUPT. The method uses building lay- out to aid the heading measurement in Kalman filter, and it could also be combined for the initial- ization. The algorithm has been investigated with real field trials using the low cost Microstrain 3DM-GX3-25 inertial sensor, a Leica GS10 GPS receiver and a uBlox EVK-6T GPS receiver. It could be concluded that the proposed method offers a significant improvement in position accuracy for the long period, allowing pedestrian navigation for nearly40 min with mean position error less than 2.8 m. This method also has a considerable effect on the accuracy of the initialization.

A Proxy Blind Signature Scheme and an Off-Line Electronic Cash Scheme

To support withdrawing and storing money from all levels of the bank for the customers in the real world, in this paper, we propose a proxy blind signature scheme and an off-line e-cash scheme based on the new proxy blind signature scheme. The pro- posed proxy blind signature is proven secure in the random oracle model under chosen-target computational Diffie-Hellman assump- tions, and the e-cash scheme can satisfy the security requirements of unforgeability, anonymity, and traceability.

Recognizing cat-eye targets with dual criterions of shape and modulation frequency

We present an image recognition method to distinguish targets with cat-eye effect from the dynamic background based on target shape and modulation frequency. Original image sequences to be processed are acquired through an imaging mechanism that utilizes a pulsed laser as active illuminator and an industrial camera as detection device. There are two criterions to recognize a target： one exploits shape priors and the other is the active illuminator＇s modulation frequency. The feasibility of the proposed method and its superiority over the single criterion method have been demonstrated by practical experiments.

Identity-Based Proxy Verifiably Encrypted Signature Scheme

A Verifiably Encrypted Signature (VES) plays an essential role in the construction of a fair data exchange. The paper proposes an Identity-based Proxy Verifiably Encrypted Signature (IPVES) to combine the advantages of a proxy signature and a VES in order to delegate the signing capability of the VES of an entity called the original signer to another entity, called the proxy signer. In this IPVES scheme, the original signer delegates his/her signing capability to the proxy signer. The proxy signer issues a signature by using a proxy signing key, encrypts the signature under a designated public key, and subsequently convinces a verifier that the resulting ciphertext contains such a signature. We prove that the proposed IPVES scheme is secure in a random oracle model under the computational Diffie-Hellman assumption.