Navigation system design using time-varying complementary filters

A new methodology for the design of navigation systems for autonomous vehicles is introduced. Using simple kinematic relationships, the problem of estimating the velocity and position of an autonomous vehicle is solved by resorting to special bilinear time-varying filters. These are the natural generalization of linear time-invariant complementary filters that are commonly used to properly merge sensor information available at low frequency with that available in the complementary region. Complementary filters lend themselves to frequency domain interpretations that provide valuable insight into the filtering design process. This work extends these properties to the time-varying setting by resorting to the theory of linear differential inclusions and by converting the problem of weighted filter performance analysis into that of determining the feasibility of a related set of linear matrix inequalities (LMIs). Using this set-up, the stability of the resulting filters as well as their "frequency-like" performance can be assessed using efficient numerical analysis tools that borrow from convex optimization techniques. The mathematical background that is required for complementary time-varying filter analysis and design is introduced. Its application to the design of a navigation system that estimates position and velocity of an autonomous vehicle by complementing position information available from GPS with the velocity information provided by a Doppler sonar system is described.     

DOA and steering vector estimation using a partially calibratedarray

We consider the problem of estimating directions of arrival (DOAs) using an array of sensors, where some of the sensors are perfectly calibrated, while others are uncalibrated. We identify a cost function whose minimizer is a statistically consistent and efficient estimator of the unknown parameters-the DOAs and the gains and phases of the uncalibrated sensors. Next we present an iterative algorithm for finding the minimum of that cost function The proposed algorithm is guaranteed to converge. The performance of the estimation algorithm is compared with the Cramer Rao bound (CRB). The derivation of the bound is also included. It is shown that DOA accuracy can be improved by adding uncalibrated sensors to a precisely calibrated array. Moreover, the number of sources that can be resolved may be larger than the number that can be resolved by the calibrated portion of the array     

Low-profile,low sidelobe array antenna with ultrawide beam coverage for UAV communication

This paper presents a design method to implement an antenna array characterized by ultra-wide beam coverage,low profile,and low Sidelobe Level (SLL) for the application of Unmanned Aerial Vehicle (UAV) air-to-ground communication.The array consists of ten broadside-radiating,ultrawide-beamwidth elements that are cascaded by a central-symmetry series-fed network with tapered currents following Dolph-Chebyshev distribution to provide low SLL.First,an innovative design of end-fire Huygens source antenna that is compatible with metal ground is presented.A low-profile,half-mode Microstrip Patch Antenna (MPA) is utilized to serve as the magnetic dipole and a monopole is utilized to serves as the electric dipole,constructing the compact,end-fire,grounded Huygens source antenna.Then,two opposite-oriented end-fire Huygens source antennas are seamlessly integrated into a single antenna element in the form of monopole-loaded MPA to accomplish the ultrawide,broadside-radiating beam.Particular consideration has been applied into the design of series-fed network as well as antenna element to compensate the adverse coupling effects between elements on the radiation performance.Experiment indicates an ultrawide Half-Power Beamwidth (HPBW) of 161°and a low SLL of-25 dB with a high gain of 12 d Bi under a single-layer configuration.The concurrent ultrawide beamwidth and low SLL make it particularly attractive for applications of UAV air-to-ground communication.     

Multiple target angle tracking using sensor array outputs

The use of the output of an array of sensors to track multiple independently moving targets is reported. The output of each sensor in the array is the sum of signals received from each of the targets. The results of direction-of-arrival estimation by eigenvalue analysis are extended to derive a recursive procedure based on a matrix quadratic equation. The solution of this matrix quadratic equation is used to provide updated target positions. A linear approximation method for estimating the solution of the matrix equation is presented. The algorithm is demonstrated by the simulated tracking of two targets. The main advantage of the algorithm is that a closed-form solution for updating the target angle estimates has been obtained. Also, its application is straightforward, and the data association problem due to uncertainty in the origin of the measurements is avoided. However, it requires the inversion of an N×N as well as other linear operations, so that the computational burden becomes substantial as N becomes very large     

Azimuth/elevation direction finding using regular array geometries

The authors consider the problem of extending the estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm for multiple source, cochannel direction finding to the two-dimensional case (e.g., azimuth and elevation angle estimation). Two algorithms are presented, one based on the optimal (minimal variance) subspace fitting formulation of ESPRIT, and the other based on an approximation to it. The algorithms are applicable to antenna arrays composed of identical subarrays displaced in two dimensions, such as uniform rectangular phased arrays. Simulation results illustrating the relative performance of the algorithms are also presented     

Flight path estimation using frequency measurements from a wideaperture acoustic array

A narrowband technique based on the acoustical Doppler effect is proposed for estimating the trajectory of a turbo-prop aircraft in level flight with constant velocity as it transits over a ground-based passive acoustic sensor array. The basic principle is to measure the temporal variation of the instantaneous frequency (IF) of the acoustic signal received by each sensor and then to minimize the sum of the squared deviations of the IF estimates from their predicted values over a sufficiently long period of time for all sensors. The technique provides estimates of the propeller blade rate and the five source motion parameters that describe the aircraft trajectory. The six dimensional minimization problem is reduced to a five dimensional maximization problem, which is solved numerically using the quasi-Newton method. A simple method is described that provides the initial parameter estimates required for the numerical maximization. The effectiveness of the motion parameter estimation technique is verified using real acoustic data recorded from a wide aperture microphone array during various transits of a turbo-prop aircraft     

Solution of the five-layer beam bending problem using the calculus of variation

The paper deals with the problem of lateral bending for the five-layer panel with the lightweight filler that is reduced to the bending problem of a beam fixed at the end sections. To solve the differential equations describing the beam bending, the Euler-Lagrange variational principle is used.     

Roll-pitch-yaw autopilot design for nonlinear time-varying missile using partial state observer based global fast terminal sliding mode control

The acceleration autopilot design for skid-to-turn (STT) missile faces a great challenge owing to coupling effect among planes, variation of missile velocity and its parameters, inexistence of a complete state vector, and nonlinear aerodynamics. Moreover, the autopilot should be designed for the entire flight envelope where fast variations exist. In this paper, a design of inte-grated roll-pitch-yaw autopilot based on global fast terminal sliding mode control (GFTSMC) with a partial state nonlinear observer (PSNLO) for STT nonlinear time-varying missile model, is employed to address these issues. GFTSMC with a novel sliding surface is proposed to nullify the integral error and the singularity problem without application of the sign function. The pro-posed autopilot consisting of two-loop structure, controls STT maneuver and stabilizes the rolling with a PSNLO in order to estimate the immeasurable states as an output while its inputs are missile measurable states and control signals. The missile model considers the velocity variation, gravity effect and parameters’ variation. Furthermore, the environmental conditions’ dynamics are mod-eled. PSNLO stability and the closed loop system stability are studied. Finally, numerical simula-tion is established to evaluate the proposed autopilot performance and to compare it with existing approaches in the literature.     

Direct position determination using single moving rotating linear array: Noncoherent and coherent processing

To improve the resolution and accuracy of Direct Position Determination (DPD),this paper investigates the problem of positioning multiple emitters directly with a single moving Rotating Linear Array (RLA).Firstly,the geometry of the RLA is formulated and analysed.According to its geometry,the intercepted noncoherent signals in multiple interception intervals are modeled.Correspondingly,the Multiple SIgnal Classification (MUSIC) based noncoherent DPD approach is proposed.Secondly,the synchronous coherent pulse signals are individually considered and formulated.And the coherent DPD approach which aims for localizing this special type of signal is presented by stacking all array responses at different interception intervals.Besides,we also derive the constrained Cramer-Rao Lower Bound (CRLB) expression for both noncoherent and coherent DPD with RLA under the constraint that the altitudes of the emitters are known.At last,computer simulations are included to examine the performance of the proposed approach.The results demonstrate that the localization accuracy and resolution of DPD with single moving linear array can be significantly improved by the array rotation.In addition,coherent DPD with RLA further improves the resolution and increases the maximum emitter number that can be localized compared with the noncoherent DPD with RLA.     

Imaging the interphase of carbon fiber composites using transmission electron microscopy:Preparations by focused ion beam,ion beam etching,and ultramicrotomy

Three sample preparation techniques, focused ion beam(FIB), ion beam(IB) etching,and ultramicrotomy(UM) were used in comparison to analyze the interphase of carbon fiber/epoxy composites using transmission electron microscopy. An intact interphase with a relatively uniform thickness was obtained by FIB, and detailed chemical analysis of the interphase was investigated by electron energy loss spectroscopy. It shows that the interphase region is 200 nm wide with an increasing oxygen-to-carbon ratio from 10% to 19% and an almost constant nitrogen-to-carbon ratio of about 3%. However, gallium implantation of FIB tends to hinder fine structure analysis of the interphase. For IB etching, the interphase region is observed with transition morphology from amorphous resin to nano-crystalline carbon fiber, but the uneven sample thickness brings difficulty for quantitative chemical analysis. Moreover, UM tends to cause damage and/or deformation on the interphase. These results are meaningful for in-depth understanding on the interphase characteristic of carbon fiber composites.