Instrument Landing Research Articles

SBAS-based navigation system for precision approach in CAT II LVC

Due to lack of advanced navigation systems, secondary airports are normally unable to support instrument approaches in low visibility conditions (LVC) more adverse than Category (CAT) I, making them inaccessible during such conditions. Incoming flights are then delayed, diverted to adjacent airports, or cancelled before take-off. This paper presents an onboard navigation solution, under development in scope of SESAR 2020 Solution PJ02-W2- 17.2, which focuses on technology development to mitigate these traffic disruptions by enabling instrument approaches in CAT II LVC with minimum airport and air navigation service provider investments. The concept builds upon global navigation satellite systems (Global Positioning System L1 frequency – GPS L1, satellite-based augmentation system), which currently enables Localizer Performance with Vertical guidance (LPV) operation down to LPV 200 minima. The designed system includes radio altimeter-based aiding and innovative integrity algorithm to improve navigation performance in support of operations below 200ft down to CAT II / LPV 100 minima. As no such requirements have yet been officially published, authors also defined sets of candidates based on Instrument Landing System Collision Risk Model and other sources. The team developed and verified a Monte-Carlo fast-time simulation toolset to enable representative and statistically significant evaluation of the concept feasibility via its availability throughout Europe, as well as sensitivity to proposed sets of alert limits. Also, flight data collection and a developed software prototype allow for further validations. Simulations demonstrated over 95% average availability with the best results achieving level of 99% depending on used set of requirements. The solution enabling operations in LVC allows unlocking various benefits to business/airline operators (e.g., avoided extra costs, increased predictability), passengers (avoided opportunity loss) and airports (retained profit from flights, less traffic at diversion airports). Technology development also marks an important step towards gate-to-gate autonomous operations.

Online Motion Planning for Fixed-Wing Aircraft in Precise Automatic Landing on Mobile Platforms

This paper proposes the creative idea that an unmanned fixed-wing aircraft should automatically adjust its 3D landing trajectory online to land on a given touchdown point, instead of following a pre-designed fixed glide slope angle or a landing path composed of two waypoints. A fixed-wing aircraft is a typical under-actuated and nonholonomic constrained system, and its landing procedure—which involves complex kinematic and dynamic constraints—is challenging, especially in some scenarios such as landing on an aircraft carrier, which has a runway that is very short and narrow. The conventional solution of setting a very conservative landing path in advance and controlling the aircraft to follow it without dynamic adjustment of the reference path has not performed satisfactorily due to the variation in initial states and widespread environmental uncertainties. The motion planner shown in this study can adjust an aircraft’s landing trajectory online and guide the aircraft to land at a given fixed or moving point while conforming to the strict constraints. Such a planner is composed of two parts: one is used to generate a series of motion primitives which conform to the dynamic constraints, and the other is used to evaluate those primitives and choose the best one for the aircraft to execute. In this paper, numerical simulations demonstrate that when given a landing configuration composed of position, altitude, and direction, the planner can provide a feasible guidance path for the aircraft to land accurately.

Estimating turbulence intensity along the glide path using wind tunnel experiments combined with interpretable tree-based machine learning algorithms

Wind fluctuations near airport runways can make aircraft landings risky. Consequently, an aircraft may veer off its glide path, missed approach, or crash. In this study, a scaled-down model of Hong Kong International Airport (HKIA) and the complex terrain in its vicinity were built in a TJ-3 atmospheric boundary layer wind tunnel to investigate wind turbulence intensity. Cobra probes were placed along the glide slope of the models' runway to compute turbulence intensity at various locations under different inflow wind directions, with and without surrounding terrain. Next, advanced tree-based machine learning algorithms, including Random Forest, Extreme Gradient Boosting, Adaptive Boosting, and Light Gradient Boosting Machine optimized via Bayesian Optimization, were used to estimate turbulence intensity along the glide path. The Bayesian optimized-random forest model outperforms all other models in prediction performance, as measured by MAE (0.521), MSE (1.046), RMSE (1.024), and R2 (0.934). Furthermore, according to SHAP analysis, "Terrain", "Distance from Runway", and "Wind Direction" significantly contributed to high turbulence intensity along the glide path. The most optimistic predictions for high turbulence intensity were the presence of complex terrain, a shorter distance from the runway, and an inflow wind direction between 125 and 200°.

Inverse optimal control for autonomous carrier landing with disturbances

This work addresses the optimal control of carrier landing affected by deck motion and airwake disturbances. Starting from aircraft dynamics written under an affine form, a novel inverse optimal control approach is designed and then used as the main control technique to provide fast and accurate tracking of the aircraft reference trajectory, as well as to improve the convergence performances and the success rate of the automatic carrier landing. A robust automatic control landing system is proposed by designing a novel inverse optimal control algorithm based on disturbance observers (for the estimation and compensation of airwake), a deck motion compensation block, and fixed-time command filters for computing the reference signals and reducing the tracking errors. The proposed optimal scheme includes a guidance controller, an attitude controller (involving the control of the heading angle, attitude angles, and angular rates), and an approach power compensation system. The proposed architecture is proved to be globally stable by using the Lyapunov theory. Finally, the comparative simulation results prove both the reliability of the control scheme and the superiority of the novel inverse optimal control technique over other nonlinear control approaches employed in the design of automatic control landing systems.

Spoof surface plasmon polariton supported by square ring metasurface for wearable body area network

A metasurface consisting of a 2D periodic square lattice of metallic square ring resonators is considered for supporting spoof surface plasmon polariton (SSPP) modes. First, SSPP modes are highlighted by simulated dispersion curves. The dispersion curves are analyzed by considering hybridization of modes in either a patch or an aperture array with frequency shifts. Hybridization of modes is also supported by means of surface current and electric field mappings showing consistent symmetric and anti-symmetric fields. Second, it is shown that a dipole antenna located near the metasurface is able to generate SSPP modes. The transmission spectra between two antennas located at each extremity of the metasurface show transmission enhancements compared with propagation in free space. The transmission enhancements are shown for different locations of the antennas either facing each other or positioned in diagonal. Finally, the transmission enhancement is connected to SSPP modes by comparing the transmission spectra and the measured dispersion curves with each other. Specifically, two transmission windows measured for an embroidered metasurface are related to the cutoff frequency of the two SSPP modes supported by the metasurface as evidenced by the measured dispersion curves.

Combining Heterogeneous Vehicles to Build a Low-Cost and Real-Time Wireless Charging Sensor Network

A wireless charging system that supports a large sensor network not only needs to provide real-time charging services but also needs to consider the cost of construction in order to meet the actual applications and considerations. The energy transfer between mobile devices is extremely difficult, especially at large distances, while at close distances a wireless, fast-charging, automatic, and high-precision landing system would be required. However, previous studies that used wireless charging cars, wireless charging unmanned aerial vehicles (UAVs) alone, or wireless charging pads to build a large-scale wireless charging system could not meet the above two conditions at the same time. If we can make good use of the existing high-speed backbone transport, such as the vehicular ad hoc network (VANET), it can not only consider the cost of construction and the speed of movement but also support the real-time charging service required by large-scale sensor networks. In this work, we propose an integration of heterogeneous mobile and charging vehicles, including VANET and UAV net, to provide a wireless rechargeable sensor network with a low-cost and high-efficiency charging system. Moreover, reward mechanisms are also designed to encourage private cars to provide transportation and charging capabilities to UAVs in the designed system.

Four decades of aviation visibility at Bhairahawa airport, gateway to Buddha's birthplace Lumbini, Nepal

Over four decades of visibility data at Bhairahawa airport (BWA), a recently upgraded international airport near Lumbini, a UNESCO heritage site in Nepal has been analyzed. In this study, we also investigated one of the important microclimatic behavior of fog i.e., onset and dispersal timings, and its implication on aviation. Temporal variations of poor visibility conditions at BWA are found to be primarily associated with variations in haze and fog. Haze at BWA accounts for the highest percentage (∼27%) of time and its annual occurrence is increasing (0.57% yr−1). There is a significant upward trend of hazy days in all seasons, the highest (1.46% day yr−1) being in post-monsoon. The overall seasonal poor visibility, too, has increased significantly in all seasons, with the highest trend in post-monsoon (1.57% yr−1). Similarly, fog frequency in the winter season has also increased noticeably for fog days (1.05% day yr−1), dense fog days (0.51% day yr−1), general fog hours (0.55% hour yr−1) and dense fog hours (0.20% hour yr−1). We found that fog at BWA is usually formed overnight and dissipates before noon. Daytime onset and late dispersion of fog are more common in the peak winter months of December and January. Further, we investigated the relationship between visibility and aerosol optical depth (AOD) and found a moderate negative correlation (r = − 0.66, p < 0.001) between them in the monsoon season. However, AOD is found to have a weaker correlation with visibility during winter (r = −0.36) and pre-monsoon (r = −0.23) seasons, when there is a more pronounced influence of meteorological conditions on the occurrence of visibility. We have observed a better correlation (r = −0.74) between fine particulate matter concentration (PM2.5) and visibility. Examining the effect of relative humidity (RH) on AOD (or, PM2.5) and visibility revealed that higher RH tends to lower visibility. Visibility at BWA airport is gradually worsening due to local and regional air pollution emissions and changing meteorological conditions. The degraded visibility at BWA airport will negatively impact flight safety and timeliness. Effective implementation of regionally coordinated air pollution mitigation measures can be a sustainable step towards the improvement of visibility in long run. However, the installation of ground equipment like CAT-II/III Instrument Landing System (ILS) for aircraft take-off and landings, and advanced surface movement guidance and control system (A-SMGCS) are highly advisable to lessen the damage potential to aviation.

Computer Modeling of the Outgoing GPR Signal

This paper considers a mathematical model to reconstruct the shape and tabular value of the source based on real signal data from a Loza-V series GPR receiver. A geoelectric equation in a cylindrical coordinate system is chosen as the mathematical model. Experiments, using GPR, were conducted on a homogeneous area of clean river sand, with known geoelectric properties. In this case, the equation in question is reduced to the Riccati differential equation using a special function substitution. This allowed us to obtain an explicit expression linking the spectrum function describing the response of the medium (the real radar data) and the spectrum function describing the source behavior. From the found source spectra, using inverse Fourier transforms, the emitted source itself is reconstructed in tabular form. The methodology of source reconstruction was carried out at different locations of the receiver antenna from the source antenna. In practice, geophysicists are interested in the physical characteristics of heterogeneity depending on spatial coordinates. For numerical solution of inverse coefficient problem it is necessary to have tabular value of disturbance source and tabular values of reflected signals (GPR data) at measurement points. To solve these problems we have developed an algorithm of source reconstruction and, as a consequence, determination of media response corresponding to real GPR data at the points of observation. A series of numerical calculations demonstrating the effectiveness of the considered computer model for source recovery have been carried out.

Favorable locations for new VGOS antennas in India depending on the assessment of geodetic parameters and environmental factors

VLBI simulation studies are carried out to investigate the impact of any proposed station or strategy on the geodetic parameters, such as Earth Orientation Parameters (EOP) and Terrestrial Reference Frame (TRF). In general, such studies are performed for making decisions on any new development in the existing VLBI network. Thus, for selecting the favorable locations for establishment of a VLBI antenna in India, simulation studies are performed on 42 potential locations to cover the whole Indian subcontinent. Furthermore, the simulation setup is divided into four scenarios that consider the current and future situations of the global VLBI network. Extensive simulation strategy is applied with optimized scheduling for each network geometry, Monte-Carlo simulations and analysis in the VieSched++ software. Since only the simulation results are thought to be insufficient for a thorough evaluation of the realistic performance of locations, environmental factors are also investigated in the current study. The environmental factors affecting the operation and vulnerability of the VLBI technique at the potential locations are also incorporated in the present study. For this, a weighted scoring model is developed with the scores and weights based on the probable impact and occurrence frequency of disrupting environmental events, respectively. This approach will avoid the possibility of new VLBI station ending up in an unfavorable location in India and, underperforming substantially in terms of the achieved improvement of geodetic parameters as determined from the simulation study. The VLBI Global Observing System (VGOS) network is being established at a global level to create a uniformly distributed network of the next generation VLBI system to meet the goals of the Global Geodetic Observing Systems (GGOS). India is planning to establish its first VGOS antenna, and therefore, this study helps to mark the high-performance favorable locations for VGOS. The improvements in geodetic parameters of favorable locations identified in the simulation study are 6.7–11.2% in the first scenario, 12.8–46.8% in second scenario, 9–20.5% in third scenario and 2.9–6.1% in fourth scenario. The favorable locations outperform other Indian locations by a factor of 1.1–5.8. In addition to that, the Indian locations having environmental factors that might affect the VGOS adversely are not portrayed as the favorable choice.Graphical

Machine-learning-estimation of high-spatiotemporal-resolution chlorophyll-a concentration using multi-satellite imagery

Chlorophyll-a concentration for quantifying phytoplankton biomass is commonly used as an indicator for evaluating the trophic level of lakes and water quality. This research aimed to develop a high spatiotemporal-resolution model for the retrieval of chlorophyll-a in inland water. Firstly, the machine learning based models considering Sentinel-2 Multispectral Instrument and Sentinel-3 Ocean and Land Color Instrument (OLCI) images were applied to estimate chlorophyll-a concentrations (R2 = 0.873 and 0.822, respectively). The spatiotemporal fusion was performed to fuse the OLCI and MSI chlorophyll-a images with low temporal resolution but fine spatial-resolution, and with high temporal resolution but coarse spatial-resolution. The random forest was applied to fuse images from two distinct sensors, and to refine the spatial resolution of OLCI estimations to be the same as those of Sentinel-2 MSI. Results showed that the spatiotemporal fusion can estimate dense-temporal 10 m spatial resolution chlorophyll-a concentration in the Tsengwen Reservoir (Root-Mean-Square Error, RMSE = 1.25–1.47 μg L−1). The spatiotemporal fusion model was effectively applied to determine high spatiotemporal-resolution chlorophyll-a measurements in the aquatic system.

Carrier Aircraft Flight Controller Design by Synthesizing Preview and Nonlinear Control Laws

This paper proposes an innovative automatic carrier landing control law for carrier-based aircraft considering complex ship motion and wind environment. Specifically, a strategy is proposed to synthesize preview control with an adaptive nonlinear control scheme. Firstly, incremental nonlinear backstepping control law is adopted in the attitude control loop to enhance the anti-disturbance capability of the aircraft. Secondly, to enhance the glide slope tracking performance under severe sea conditions, the carrier motion is predicted, and the forecasted motion is adopted in an optimal preview control guidance law to compensate influences induced by carrier motion. However, synthesizing the inner-loop and outer-loop control is not that straightforward since the preview control is naturally an optimal control law which requires a state-space model. Therefore, low-order equivalent fitting of the attitude-to-altitude high-order system model needs to be performed; furthermore, a state observer needs to be designed for the low-order equivalent system to supply required states to the landing controller. Finally, to validate the proposed methodology, an unmanned tailless aircraft model is used to perform the automatic landing tasks under variant sea conditions. Results show that the automatic carrier landing system can lead to satisfactory landing precision and success rate even under severe sea conditions.

Fault-Tolerant Control for Carrier-Based UAV Based on Sliding Mode Method

To enable a carrier-based unmanned aerial vehicle (UAV) to track the desired glide trajectory and safely land on the deck with the presence of system faults, this paper proposes a neural network-based adaptive sliding mode fault-tolerant control (NASFTC) method. Firstly, the dynamic model of the carrier -based UAV, the actuator fault model, the additional unknown fault model, and the control framework of the automatic carrier landing system (ACLS) were developed. Subsequently, controllers for both longitudinal and lateral channels were designed by using the NASFTC method. The controller consists of three parts: the adaptive laws for compensating the actuator faults, the RBF neural network for compensating the additional unknown faults, and the sliding mode method for ensuring overall trajectory tracking. Then, the Lyapunov function theorem was applied to carry out the stability analysis. Finally, comparative simulations under three different scenarios were conducted. The comparative results show the effectiveness of the proposed NASFTC method, which has fault-tolerant ability and can successfully control the aircraft to execute carrier landing task regardless of the actuator partial loss fault and the additional unknown fault.

MC-LRF based pose measurement system for shipborne aircraft automatic landing

Due to the portability and anti-interference ability, vision-based shipborne aircraft automatic landing systems have attracted the attention of researchers. In this paper, a Monocular Camera and Laser Range Finder (MC-LRF)-based pose measurement system is designed for shipborne aircraft automatic landing. First, the system represents the target ship using a set of sparse landmarks, and a two-stage model is adopted to detect landmarks on the target ship. The rough 6D pose is measured by solving a Perspective-n-Point problem. Then, once the rough pose is measured, a region-based pose refinement is used to continuously track the 6D pose in the subsequent image sequences. To address the low accuracy of monocular pose measurement in the depth direction, the designed system adopts a laser range finder to obtain an accurate range value. The measured rough pose is iteratively optimized using the accurate range measurement. Experimental results on synthetic and real images show that the system achieves robust and precise pose measurement of the target ship during automatic landing. The measurement means error is within 0.4° in rotation, and 0.2% in translation, meeting the requirements for automatic fixed-wing aircraft landing.Received 5 July 2022; revised 19 August 2022; accepted 27 September 2022.

Control of autonomous UAV using an onboard LSTM neural network

Towards realising autonomous UAVs, this paper investigates one of the fundamental autonomous flying research problems, i.e., the ability of a vehicle to control its flying behaviour autonomously, without reliance on external infrastructure like Instrument Landing Systems or GPS. In this paper we experiment with a physical UAV prototype with embedded intelligent control capabilities, utilising a Long Short Term Memory (LSTM) neural network, in order to learn lift-off control sequences using self-training. The initial results are promising and show potential for embedding LSTMs in the control systems of autonomous UAVs.

The necessity of flight calibration temperature correction of high plateau airport instrument landing system

The necessity of flight calibration temperature correction of high plateau airport instrument landing system

Analysis of Antenna Locations (Roof, Fender, and Bumper) at 28 GHz in a Suburban Environment for V2I using SISO and MIMO Antenna Configurations

Analysis of Antenna Locations (Roof, Fender, and Bumper) at 28 GHz in a Suburban Environment for V2I using SISO and MIMO Antenna Configurations

Joint antenna selection and waveform design for coexistence of MIMO radar and communications

As the problem of spectral congestion is becoming severe, the coexistence between two primary spectrum users, radar and communications, has spurred extensive research interest. To reduce the mutual interferences between the two functions, MIMO radar waveform design needs to consider the compatibility in both spectral and spatial domains, where the former is achieved by null forming in the frequency domain and the latter is achieved by shaped beampattern synthesis. Additionally, high power efficiency and low system overhead are two desirable characteristics for MIMO radar system design. To this end, we first introduce a new realistic waveform constraint, peak-to-valley-power-ratio (PVPR) constraint per antenna to improve the power efficiency. Then, combined with PVPR constraint, we propose a switchable individual antenna power control scheme to jointly optimize waveforms and antenna locations. We adopt a max–min beampattern matching criterion and impose the ell _{2,1}-norm penalty on the waveform matrix to promote the sparsity of the array. To solve the resultant non-smooth and non-convex problem, we develop a modified alternating directions method of multipliers, where a surrogate subproblem over primal variables is solved instead of the original problem, and its local convergence is analyzed. Finally, numerical experiments demonstrate the effectiveness and superiority of the proposed method over counterparts, especially obtaining the lowest sidelobe level and deeper spectral nulls using much fewer antennas.

Inversion and Monitoring of the TP Concentration in Taihu Lake Using the Landsat-8 and Sentinel-2 Images

Eutrophication is a significant factor that damages the water ecosystem’s species balance. The total phosphorus (TP) concentration is a vital water quality indicator in assessing surface water eutrophication. This paper predicts the spatial distribution of TP concentration using remote sensing, measured data, and the partial least squares regression (PLSR) method. Based on the correlation analysis, the models were built and tested using the TP concentration and Sentinel-2 Multispectral Instrument (MSI) and Landsat-8 Operational Land Imager (OLI) image spectra. The results demonstrated that the best technique based on band combinations of the Sentinel-2 and Landsat-8 images achieved good precision. The coefficient of determination (R2), root mean square error of prediction (RMSEP), and residual prediction deviation (RPD) were 0.771, 0.023 mg/L, and 2.086 for Sentinel-2 images and 0.630, 0.032 mg/L, and 1.644 for Landsat-8 images, respectively. The TP concentration maps were interpolated using the inverse distance weighting method, and the inversion results obtained from the images were in good agreement. The western and northwestern regions of Taihu Lake, where significant cyanobacterial blooms occurred, had TP concentrations greater than 0.20 mg/L; nevertheless, the central and eastern regions had amounts ranging from 0.05 to 0.20 mg/L. In order to prove the extensibility of the model, the optimal algorithm was applied to the Sentinel-2 and Landsat-8 images in 2017. The optimal algorithm based on Landsat-8 images has a better verification effect (RMSEP = 0.027 mg/L, and R = 0.879 for one Landsat-8 image), and the optimal algorithm based on Sentinel-2 images has moderate verification effect (RMSEP = 0.054 mg/L and 0.045 mg/L, and R = 0.771 and 0.787 for two Sentinel-2 images). The interpolation and inversion maps are in good agreement, indicating that the model is suitable for the Landsat-8 and Sentinel-2 images, which can be complementary for higher temporal resolutions. Monitoring water quality using multiple remote sensing images can provide the scientific basis for water quality dynamic monitoring and prevention in China.

Investigation of Radio Frequency Signal Propagation of Wireless Services in Oyo, Oyo State, South Western Nigeria

This study reported the investigation of the Radio Frequency (RF) signal propagation of Global System for Mobile Communications (GSM) coverage in Emmanuel Alayande College of Education (EACOED), Oyo, Oyo State, Nigeria. The study aims at amplifying the quality of service and augment end users' sensitivity of the wireless services operation. The drive test method is adopted with estimation of coverage level and received signal strength. The Network Cell Info Lite application installed in three INFINIX GSM mobile phones was employed to take the measurement of the signal strength received from the transmitting stations of different mobile networks. The results of the study revealed that MTN has the maximum signal strength with a mean value of - 68.33 dBm, directly followed by Globacom (-80.41 dBm) and Airtel with -83.13 dBm. The Airtel signal has a conspicuously invariable poor performance with coverage level of 41.66 %. Conversely, the MTN and Globacom signal reception are observed to surpass the Airtel network within the college premises with 83.33 % and 60.41 % coverage level respectively. This implies that the signal quality for MTN and Globacom networks were comparatively disseminated within the college with inconsequential fluctuations in quality while Airtel signal is subsided and weaken. The poor performance in some areas was due to the presence of physical impediments and far distances location of base station antennas in the promulgation locations. This study therefore suggested that Airtel and Globacom Base Transceiver Stations (BTS) should be positioned within the college to improve good network reportage level.

Location Based Services for Remote Education and Health Institutes Using Sum-Difference Signal Patterns

This paper presents a simple approach to providing location-based services (LBSs) for the remotely located educational and health institutes on demand, particularly in emergency situations i.e., COVID-19, using an antenna array. The proposed approach consists of the sum and difference patterns of the signal obtained from the antenna array at the base station of a wireless network. It provides the location of the targeting institute i.e., education and health, in terms of the angle-of-arrival (AoA) which can be used to steer the radiation beam in the targeted direction in order to provide the desired services i.e., emergency wireless communication link. In this way, fast and high bandwidth-based communication and networking can be possible for the mentioned organizations. We show antenna array design and location finding results in this paper. The obtained results in terms of antenna parameters and AoA show that the proposed approach is efficient, less complicated, and can be implemented in the next-generation wireless networks i.e., AI-enabled IoT and 5G systems, particularly for the educational and health institutes.