Flight Parameter Estimation Research Articles

A Variable Gain Complementary Filtering Fusion Algorithm Based on Distributed Inertial Network and Flush Air Data Sensing

Aiming at the problem that the accuracy of flight parameters calculated by the traditional flush air data sensing (FADS) and inertial navigation system (INS) complementary filter cannot meet the fine real-time control of the aircraft, a data fusion algorithm based on distributed inertial network and FADS is proposed. This method converts the inertial navigation parameters calculated by the distributed inertial network into flight parameters, and using the least squares fitting theory, the flight parameters are obtained from the pressure data measured by the FADS pressure hole. Then, by adjusting the filter constant of the complementary filtering algorithm, the flight parameters calculated by the inertial network are fused with the flight parameters calculated by the air data sensing to obtain high-precision flight parameters. Finally, the simulation results show that the proposed filtering algorithm can keep the flight parameter estimation error less than 0.01 degrees throughout the flight phase. Compared with the traditional complementary filter, the estimation error of the proposed algorithm is smaller.

Parallel crosschecking neural network based fault-tolerant flight parameter estimation and faulty sensor identification

Reliable flight parameter estimation is crucial for the safe operation of unmanned air vehicles. Recent studies on flight parameter estimation based on distributed airflow sensors have shown promising results; however, how to extract reliable flight parameters and locate faults in case of sensor failures are not studied yet. This paper proposes a novel fault-tolerant flight parameter estimation method with capabilities to identify and isolate faulty sensors for a flight parameter estimation system based on distributed airflow sensors. First, the distributed sensors are grouped into subsets using combinations. Second, feedforward backpropagation neural networks of the same structure are designed and used by all subsets for flight parameter estimation. The crosschecking between these parallel networks improves the robustness of the estimation. In case of sensor failures, the sensor groups that contain any faulty sensors will result in wrong flight parameter estimations. Especially, a directional random sample consensus algorithm is developed and used to identify the subsets that contain faulty sensors. Then, the ratio of the faulty subsets is used to identify the number of faulty sensors. Finally, the faulty sensors will be identified according to the frequencies of their appearance in the subsets that contain faulty sensors. The effectiveness of the proposed method is validated by using wind tunnel tests. The results show that the proposed method can effectively provide reliable flight parameters and identify faulty sensors.

Parametermeasurement of aircraft-radiated noise from a single acoustic sensor node in three-dimensional space

A line spectrum presents the form of a narrow-band time-varying signal due to Doppler effect when the single hydrophone node observes flight-radiated noise. The modulation law of the time-varying signal contains a large number of feature information of moving targets, which can be used for detection and classification. This paper studies the possibility of using instantaneous frequency measurements from the hydrophone node to improve the precision of the flight parameter estimates when the source spectrum contains a harmonic line of constant frequency. First of all, we build up and analyze the underwater sound field excited by the aircraft using the ray theory model; then the Doppler shift in the two isospeed media, which is caused by the aircraft, is established; finally, a robust time–frequency transform describes the time–frequency distribution of the received signal, and a geometric approach solves the flying parameters.

Estimating the flight parameters of a moving airborne source using one hydrophone

The low frequency tone noise of the turboprop aircrafts can be discovered more easily under water than the broadband continuum spectrum noise due to its higher intensity. Ferguson and Lo provided a method based on a single hydrophone for estimating the four flight parameters, including the source frequency, velocity, altitude and CPA time (the time when the source passes the closet point of approach), using the variation of the instantaneous frequency (IF) of a single tone over time [Ferguson and Lo, IEEE J. Oceanic Eng., 24(4):424–435 (1999)]. Therefore, the performance of their method is largely determined by the precision of the IF estimates, which were obtained by using the short-time Fourier transform (STFT). In this paper, the polynomial chirplet transform (PCT), which models the change of the IF over time as a polynomial, is used instead of STFT to provide more accurate IF estimates. Moreover, multiple tones are used to improve the precision of the flight parameter estimates. The performance improvement is demonstrated by simulations and an experiment carried out near the Sanya coast in May, 2018.

Flight parameter estimation using instantaneous frequency and direction of arrival measurements from a single acoustic sensor node

When an airborne sound source travels past a stationary ground-based acoustic sensor node in a straight line at constant altitude and constant speed that is not much less than the speed of sound in air, the movement of the source during the propagation of the signal from the source to the sensor node (commonly referred to as the "retardation effect") enables the full set of flight parameters of the source to be estimated by measuring the direction of arrival (DOA) of the signal at the sensor node over a sufficiently long period of time. This paper studies the possibility of using instantaneous frequency (IF) measurements from the sensor node to improve the precision of the flight parameter estimates when the source spectrum contains a harmonic line of constant frequency. A simplified Cramer-Rao lower bound analysis shows that the standard deviations in the estimates of the flight parameters can be reduced when IF measurements are used together with DOA measurements. Two flight parameter estimation algorithms that utilize both IF and DOA measurements are described and their performances are evaluated using both simulated data and real data.

Flight parameter estimation using instantaneous frequency and time delay measurements from a three-element planar acoustic array.

The acoustic signal emitted by a turbo-prop aircraft consists of a strong narrowband tone superimposed on a broadband random component. A ground-based three-element planar acoustic array can be used to estimate the full set of flight parameters of a turbo-prop aircraft in transit by measuring the time delay (TD) between the signal received at the reference sensor and the signal received at each of the other two sensors of the array over a sufficiently long period of time. This paper studies the possibility of using instantaneous frequency (IF) measurements from the reference sensor to improve the precision of the flight parameter estimates. A simplified Cramer-Rao lower bound analysis shows that the standard deviations in the estimates of the aircraft velocity and altitude can be greatly reduced when IF measurements are used together with TD measurements. Two flight parameter estimation algorithms that utilize both IF and TD measurements are formulated and their performances are evaluated using both simulated and real data.

Inflow Prediction and First Principles Modeling of a Coaxial Rotor Unmanned Aerial Vehicle in Forward Flight

When the speed of a coaxial rotor helicopter in forward flight increases, the wake skew angle of the rotor increases and consequently the position of the vena contracta of the upper rotor with respect to the lower rotor changes. Considering ambient air and the effect of the upper rotor, this study proposes a nonuniform inflow model for the lower rotor of a coaxial rotor helicopter in forward flight. The total required power of the coaxial rotor system was compared against Dingeldein’s experimental data, and the results of the proposed model were well matched. A plant model was also developed from first principles for flight simulation, unknown parameter estimation and control analysis. The coaxial rotor helicopter used for this study was manufactured for surveillance and reconnaissance and does not have any stabilizer bar. Therefore, a feedback controller was included during flight test and parameter estimation to overcome unstable situations. Predicted responses of parameter estimation and validation show good agreement with experimental data. Therefore, the methodology described in this paper can be used to develop numerical plant model, study non-uniform inflow model, conduct performance analysis and parameter estimation of coaxial rotor as well as other rotorcrafts in forward flight.

An overview of the FP7 RECONFIGURE project: industrial, scientific and technological objectives

This paper details the industrial challenges, goals and objectives of the European Framework 7th project termed “REconfiguration of CONtrol in Flight for Integral Global Upset REcovery” (RECONFIGURE). This project aims at investigating and developing advanced aircraft Guidance, Navigation and Control (GNC) technologies that facilitate the automated handling of off-nominal events and optimize the aircraft status and flight. These technologies will extend the operation of the current GNC functionalities that assist the pilot and optimize the aircraft performance. Thus, the aim is to provoke a change in aircraft transport towards: “Full-time, all-event availability of performance-enhancement electrical fly-by-wire”. Three key enablers have been identified for moving towards this new paradigm: Flight Parameter Estimation, Fault Detection and Diagnosis, and Fault Tolerant Control.

Flight parameter estimation using time delay and intersensor multipath delay measurements from a small aperture acoustic array

A ground-based acoustic sensor array can be used to estimate the complete set of flight parameters of a jet aircraft or other airborne source of broadband sound in transit by measuring the differential time of arrival (DTOA), or the time delay, of the direct path signal at each sensor pair of the array over a sufficiently long period of time. This paper studies the possibility of using intersensor multipath delay measurements to improve the precision of the flight parameter estimates for a small aperture array, without increasing the array's intersensor spacing or the observation time for more time delay measurements. Intersensor multipath delay is defined as the DTOA of the direct path signal at one sensor and the ground-reflected path signal at another sensor. The flight parameter estimation algorithm is formulated and a simplified Cramer-Rao lower bound error analysis is presented, which shows that the standard deviations in the flight parameter estimates are greatly reduced when intersensor multipath delay measurements are used together with time delay measurements. The effectiveness of the proposed flight parameter estimation method for small aperture arrays is verified using both simulated and real data.

Coherent MapDrift Technique

A new parametric autofocus technique with a high accuracy of flight-parameter estimation dedicated to strip-mode synthetic aperture radar (SAR) systems is presented. Most of the known autofocus techniques require high-reflectivity targets (man-made targets) to obtain a properly focused SAR image. The technique proposed in this paper allows flight parameters to be estimated effectively, even for a low-contrast scene (e.g., forests, fields, small paths, etc.). The autofocus technique is based on well-known MapDrift (MD) principles. The presented technique is a coherent one, which allows flight parameters to be estimated more precisely than in the other well-known parametric technique referred to as classical MD. The presented technique allows flight parameters to be estimated with accuracy that is independent of the initial velocity error. It can be used for real-time processing for both Earth imaging and moving-target indication.

Aircraft flight parameter estimation using acoustical Lloyd's mirror effect

A model is developed for the acoustical Lloyd's mirror effect observed in the output time-frequency distribution of a microphone located near the ground during the transit of a jet aircraft. The feasibility of using this effect for flight parameter estimation is assessed by a simple Cramer-Rao lower bound analysis. The nonlinear least-squares method and the generalized Hough transform method are formulated for flight parameter estimation. The performances of both methods are evaluated and compared using real acoustic data.

Aircraft flight parameter estimation based on passive acoustic techniques using the polynomial Wigner–Ville distribution

The acoustic signal from an overflying aircraft, as heard by a stationary observer, is used to estimate an aircraft’s constant height, ground speed, range, and acoustic frequency. Central to the success of this flight parameter estimation scheme is the need for an accurate estimate of the instantaneous frequency of the observed acoustic signal. In this paper, the polynomial Wigner–Ville distribution is used in this application as the instantaneous frequency estimator. Its performance and the issue of the optimal time domain window length are addressed.