Estimation Of Signal Parameters Via Rotational Invariance Techniques Research Articles

Building Characterization Using L-Band Polarimetric Interferometric SAR Data

This letter proposes a building characterization technique for L-band polarimetric interferometric synthetic aperture radar (SAR) data. This characterization consists of building identification and height estimation. Initially, a polarimetric interferometric segmentation is performed to isolate buildings from their surroundings. This classification identifies three basic categories: single bounce, double bounce, and volume diffusion. In order to compensate for the misclassifications among the volume and the double-bounce classes, interferometric phases given by the high-resolution Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT) method are analyzed. Once buildings are localized, a phase-to-height procedure is applied to retrieve building height information. The method is validated using E-SAR, German Aerospace Center (DLR) fully polarimetric SAR data, at L-band, repeat-pass mode, over the Oberpfaffenhofen, Germany, test site, with a spatial resolution of 1.5 m in range and azimuth. More than 80% of buildings are retrieved with acceptably accurate height estimates.

Compensation for the mutual coupling effect in the ESPRIT direction finding algorithm by using a more effective method

An effective method is introduced to compensate for the mutual coupling effect in the estimation of signal parameter via rotational invariance techniques (ESPRIT) direction finding algorithm. The compensation method seeks to quantify the mutual coupling more accurately by using a new mutual impedance. Study of two closely spaced arriving signals shows that the high-resolution capability of ESPRIT can be achieved only when the mutual coupling effect is compensated for by using our new compensation method. Critical situations with a large signal level difference, with an increased mutual coupling effect resulting from a more compact-size antenna array, and with signals coming from a nonhorizontal elevation angle are also studied using the ESPRIT algorithm. Results show that the new compensation method, when applied to ESPRIT, is more accurate, more robust, and more flexible than the previous open-circuit voltage method.

An ESPRIT-like algorithm for coherent DOA estimation

Conventionally, the approaches to coherent direction-of-arrival (DOA) estimation are to eliminate the rank loss of the spatial covariance matrix. In this letter, a new technique is presented from another point of view, which reconstructs a special antenna array model based on the Toeplitz matrix whose rank is only related to the DOA of signals and cannot be affected by the coherency between them. Therefore, the signal and noise subspaces can be estimated properly. In conjoint with the improved estimation of signal parameter via rotational invariance techniques (ESPRIT) algorithm, it is capable of resolving the DOAs of coherent signals as well as uncorrelated signals without peak searching. The numerical examples demonstrate its validity.

Application of ESPRIT in broad beam HF ground wave radar sea surface current mapping

HF surface wave radar system OSMAR2000 is a broad-beam sea-state detecting radar. ESPRIT (Estimation of Signal Parameters via Rotational Invariance Technique) algorithm is proposed to apply in DOA (direction of arrival) determination of sea echoes. The algorithm of ESPRIT is briefly introduced first. Then discussions are made on the technique for application in the OSMAR2000 framework. Numerical simulation results are presented to demonstrate the feasibility of radial current mapping based on this method. The algorithm manifests significant performance and computational advantages compared with that of MUSIC. Data acquired by OSMAR2000 are processed to give radial current map and the synthesized vector currents are compared with the in-situ measurement with traditional means. The results show the validity of ESPRIT application in DOA determination for broad-beam radar.

Two-Dimensional ESPRIT With Tracking for Radar Imaging and Feature Extraction

Estimation of signal parameters via rotational invariance techniques (ESPRIT) appears to be the best of the known spectral-analysis methods. It has the highest resolution, has no spectral splatter and is robust in the presence of noise. It answers immediately and explicitly the question "What frequencies, real or complex, are present and what are their amplitudes?" Fourier methods (and other high-resolution methods), answer the less direct question "What amplitudes, applied to a set of regularly-spaced real frequencies, best represent the data?" They then present the problem of interpreting the amplitudes. These attributes of ESPRIT, in the two-dimensional (2-D) version described here, make it a natural for radar signal processing, where it answers the need for high-resolution imaging, free of sidelobes in range and range rate, and for high-fidelity feature extraction. The paper starts with the mathematical data model, describes a "resampling" procedure to fit the data better to the model, summarizes the 2-D ESPRIT algorithm itself, and presents examples of its performance. The paper covers the details of this least-squares version of ESPRIT, including an enhancement that allows the scatterers to be tracked individually. The algorithm properly distinguishes between scatterers having one coordinate in common, and it automatically pairs correctly the range and range-rate of each scatterer.

Ambiguity in MUSIC and ESPRIT for direction of arrival estimation

The MUltiple SIgnal Classification (MUSIC) and Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT) algorithms produce an ambiguity in the estimated direction-of-arrival results, when the antenna element spacing on a linear array is more than half a wavelength. The reason for this is investigated.

Signal parameter estimation via the Cayley-Hamilton constraint

The estimation of signal parameters via rotational invariance technique (ESPRIT) algorithm has proved to be a robust solution to exploit single invariance structure in array elements. However, ESPRIT is not flexible to incorporate multiple invariances. A closed form solution to the problem of estimating eigenvalues in multiple invariant structures is presented in this paper. It is shown that the algorithm is comparable in complexity to ESPRIT but performs better than ESPRIT, especially when only a limited number of signal samples are available. In addition, the algorithm is shown to be feasible even for single array elements sharing multiple invariance.

The double-directional radio channel

We introduce the concept of the double-directional mobile radio channel. It is called this because it includes angular information at both link ends, e.g., at the base station and at the mobile station. We show that this angular information can be obtained with synchronized antenna arrays at both link ends. In wideband high-resolution measurements, we use a switched linear array at the receiver and a virtual-cross array at the transmitter. We evaluate the raw measurement data with a technique that alternately used estimation and beamforming, and that relied on ESPRIT (estimation of signal parameters via rotational invariance techniques) to obtain superresolution in both angular domains and in the delay domain. In sample microcellular scenarios (open and closed courtyard, line-of-sight and obstructed line-of-sight), up to 50 individual propagation paths are determined. The major multipath components are matched precisely to the physical environment by geometrical considerations. Up to three reflection/scattering points per propagation path are identified and localized, lending insight into the multipath spreading properties in a microcell. The extracted multipath parameters allow unambiguous scatterer identification and channel characterization, independently of a specific antenna, its configuration (single/array), and its pattern. The measurement results demonstrate a considerable amount of power being carried via multiply reflected components, thus suggesting revisiting the popular single-bounce propagation models. It turns out that the wideband double-directional evaluation is a most complete method for separating multipath components. Due to its excellent spatial resolution, the double-directional concept provides accurate estimates of the channel's multipath-richness, which is the important parameter for the capacity of multiple-input multiple-output (MIMO) channels.

2-D spatial smoothing for multipath coherent signal separation

The use of two-dimensional spatial smoothing (SS) to increase channel capacity of wireless communications system is discussed, The necessary and sufficient conditions on array configuration for applying SS to multiple signal classification (MUSIC), and adaptive beamforming algorithms are defined and proved, This array must have an orientational invariance structure with an ambiguity free center array, and the number of subarrays must be larger than or equal to the size of the largest group of coherent signals. We also studied the cause of ambiguities in a multipath environment. We found the necessary and sufficient conditions for a three-sensor array manifold to be ambiguity free and identified several higher order ambiguity situations, If an array is also central symmetric, the forward/backward SS (FBSS) can be used to improve the resolution. Finally, we extended our results to the estimation of signal parameters via rotational invariance techniques (ESPRIT). All the predicted results are verified by simulations.

Multimode parameter extraction for multiconductor transmission lines via single-pass FDTD and signal-processing techniques

We present two approaches to extract the broadband multimode parameters of guided wave structures from a single-pass finite-difference time-domain (FDTD) simulation. They include a two-dimensional (2-D) Fourier transform (FT) algorithm and a super-resolution estimation of signal parameters via rotational invariance technique (ESPRIT) algorithm. Comparison is made to show the superiority of the super-resolution approach. As a typical application, a three-line coupled microstrip structure is studied. After a single-pass FDTD simulation, broadband multimode parameters such as propagation constants, modal-field templates, and modal impedances are extracted and verified against published data obtained by the spectral-domain method. The main feature of this parameter-extraction methodology is that it decouples the computational electromagnetics engine (in this case, the FDTD simulator) from the post-processing parameter-extraction algorithm, thus providing more flexibility and connectivity among the various simulation tools.

Further study of the Pencil-MUSIC algorithm

For finding 2-D angles and polarizations of waves arriving at a rectangular array of crossed dipoles, the Pencil-MUSIC method can achieve the near optimum performance with much less computational burden than the MUSIC (multiple signal classification). Following an angle-only ESPRIT (estimation of signal parameters via rotational invariance techniques) method, an angle-only Pencil-MUSIC can be easily formulated which is far more accurate than the former especially in the coherent case. The angle-only Pencil-MUSIC is analyzed and compared with the original Pencil-MUSIC. The new version sacrifices the polarization estimation to achieve about 8 times more efficient computation The accuracy of the new version seems no more than 4 times worse in terms of estimation deviation.

On a Novel Subspace-Based Approach to Parameter Estimation

A novel method for the estimation of temporal or spatial frequencies from measurements corrupted by additive white noise has been recently proposed in this journal. In the present paper we rederive that method in a more direct way than in the original work. Our simple derivation makes it possible to relate the subject method to the estimation-of-signal-parameters-via-rotational-invariance-techniques (ESPRIT). We show that ESPRIT and the new method under discussion are identical in finite samples, for a sensible choice of the user′s variable in the latter technique. We also discuss the use of centrohermitian sample covariances with the previous two methods or, in fact, any other eigenanalysis-based frequency estimator.

ESPRIT Direction-of-Arrival Estimation in the Presence of Spatially Correlated Noise

An algorithm is presented for ESPRIT (estimation of signal parameters via rotational invariance techniques) direction of arrival estimation when the expected value of the covariance of the measurement noise is different from a constant multiple of an identity matrix. The algorithm is based on a modification of the generalized singular value decomposition (GSVD) of two data matrices and requires only unitary transformations. The modification results in a significant simplification of the GSVD-based ESPRIT algorithm and produces more accurate solutions than prewhitening.

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. >

Sensitivity analysis of DOA estimation algorithms to sensor errors

A unified statistical performance analysis using subspace perturbation expansions is applied to subspace-based algorithms for direction-of-arrival (DOA) estimation in the presence of sensor errors. In particular, the multiple signal classification (MUSIC), min-norm, state-space realization (TAM and DDA) and estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithms are analyzed. This analysis assumes that only a finite amount of data is available. An analytical expression for the mean-squared error of the DOA estimates is developed for theoretical comparison in a simple and self-contained fashion. The tractable formulas provide insight into the algorithms. Simulation results verify the analysis.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

An experimental investigation of three eigen DF techniques

The comparative direction-finding (DF) performance of multiple signal classification (MUSIC), ROOT-MUSIC, and estimation of signal parameters via rotational invariance techniques (ESPRIT) is considered. Data were collected from two target transmitters operating simultaneously. The objective of the experiment was to evaluate multipath resolution capability using measurement precision equivalent to that found in modern radio direction-finding systems. >

Two-dimensional angle and polarization estimation using the ESPRIT algorithm

It is shown how the ESPRIT (estimation of signal parameters via rotational invariance techniques) algorithm may be used with a square array of crossed dipoles to estimate both the two-dimensional arrival angles and the polarization of incoming narrowband signals. The ESPRIT algorithm exploits the invariance properties of such an array so that both angle and polarization estimates may be computed. Some typical examples showing the use of this approach are presented.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Improving ESPRIT via beamforming

Beamforming techniques are presented that improve the performance of the ESPRIT (estimation of signal parameters via rotational invariance techniques) algorithm for solving the narrowband multiple source location problem with uniform linear arrays. Using ESPRIT with these beamforming approaches maintains the computational advantage of the original ESPRIT while further exploiting the special structure of uniform linear arrays. Simulation results show that the use of ESPRIT with beamforming yields significantly improved performance compared with the original ESPRIT.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Angle and polarization estimation using ESPRIT with a polarization sensitive array

It is shown how estimation of signal parameters via rotational invariance techniques (ESPRIT) may be used to estimate both the arrival directions and the polarizations of incoming plane waves with a uniform linear array of crossed dipoles. The ESPRIT algorithm exploits the invariance properties of such an array so that both angle and polarization estimates may be computed. Some typical examples showing the use of this method are presented. >

On the sensitivity of the ESPRIT algorithm to non-identical subarrays

ESPRIT (estimation of signal parameters via rotational invariance techniques) is a recently introduced algorithm for narrowband direction-of-arrival (DOA) estimation. Its principal advantage is that the DOA parameter estimates are obtained directly, without knowledge (and hence storage) of the array manifold and without computation or search of some spectral measure. This advantage is achieved by constraining the sensor array to be composed of two identical, translationally invariant subarrays. In this paper, we analyse the sensitivity of ESPRIT to the assumption that the subarrays are identical. The analysis is applicable to a wide variety of array errors, including non-identical angle-dependent and angle-independent gain and phase perturbations, errors in the locations of the subarray elements, and mutual coupling effects. A representative simulation example will be presented to validate the analysis and compare the performance degradation of ESPRIT with that of the MUSIC algorithm.