Inder J. Gupta

Effect of mutual coupling on the performance of adaptive arrays

The effect of mutual coupling between array elements on the performance of adaptive arrays is examined. The study includes both steady state and transient performance. An expression for the steady state output signal-to-interference-plus-noise ratio (SINR) of adaptive arrays, taking into account the mutual coupling between the array elements, is derived. The expression is used to assess the steady state performance of adaptive arrays. The transient response is studied by computing the eigenvalues associated with the signal covariance matrix. The steering vector required to maximize the output SINR of Applebaum-type adaptive arrays in the presence of mutual coupling is also given.

A novel signal processing technique for clutter reduction in GPR measurements of small, shallow land mines

A signal processing technique is developed to reduce clutter due to ground bounce in ground penetrating radar (GPR) measurements. This technique is especially useful when a GPR is used to detect subsurface antipersonnel mines. The GPR clutter is modeled using a simple parametric model. Buried mine and clutter contributions are separated through a pair of coupled iterative procedures. The algorithm outperforms existing clutter reduction approaches and also yields target features that are useful for detection and identification of these mines. The proposed technique effectively reduces clutter resulting in a significant decrease in false alarm rates.

A parametric model for synthetic aperture radar measurements

We present a parametric model for radar scattering as a function of frequency and aspect angle. The model is used for analysis of synthetic aperture radar measurements. The estimated parameters provide a concise, physically relevant description of measured scattering for use in target recognition, data compression and scattering studies. The scattering model and an image domain estimation algorithm are applied to two measured data examples.

High-resolution radar imaging using 2-D linear prediction

An algorithm for radar imaging is described. The algorithm is based on two-dimensional (2-D) linear prediction of 2-D Cartesian frequency spectra. It is shown that the algorithm provides much better resolution than the ISAR image obtained using a 2-D inverse Fourier transform. The algorithm is especially useful for imaging targets using small-bandwidth RCS data over limited aspect angle regions. >

An experimental study of antenna array calibration

The coupling matrix concept for predicting the radiation patterns of elements of an antenna array is studied. Measured data, as well as some numerical data, are used in the study. It is demonstrated that for some practical antennas of interest whose radiation patterns are affected by structure scattering, the coupling matrix concept may not work very well. As expected, the stronger the structure scattering, the greater the discrepancy between the predicted patterns and the actual patterns.

Data extrapolation for high resolution radar imaging

In radar imaging, AR modeling is sometimes used to extrapolate the scattered field data to obtain a high resolution image. In general, the Burg method is used to estimate the prediction parameters. The Burg method leads to a stable prediction filter but can also cause bias in the estimated spectra. One can also use the modified covariance method (MCM) to estimate the prediction parameters. These parameters lead to unbiased spectra. However, the MCM does not guarantee a stable prediction filter. One may have to modify the prediction parameters to ensure a stable prediction filter. One way to ensure stability is to reflect the unstable poles inside the unit circle. It is shown that the modified parameters can be used effectively for data extrapolation. The radar images obtained using this extrapolated data are more accurate than those obtained using the extrapolated data from the Burg prediction parameters. >

Dependence of adaptive array performance on conventional array design

A direct relationship between conventional array design and the array performance in an adaptive mode is given. It is shown that the basic goals of conventional array design such as low sidelobes and narrow beamwidth have a direct effect on the adaptive array performance and should not be ignored. Expressions are obtained showing that the output signal-to-interference-plus-noise ratio (SINR) of an adaptive array is related to the conventional pattern of the array. These expressions allow the prediction of the performance of an array in its adaptive mode given its conventional electromagnetic characteristics. Thus, they are an important design tool for adaptive arrays. The relations between the conventional and adaptive array are illustrated for linear and circular arrays.

Application of maximum likelihood estimation to radar imaging

An efficient maximum likelihood (ML) estimator to obtain the scattering center locations of a target and the relative scattering level of these scattering centers from the scattered field data is described. In the proposed method, ML estimation is carried out in the image domain rather than in the frequency-aspect domain. A two-dimensional (2-D) inverse Fourier transform is used to transfer the scattered field data from frequency-aspect domain to the image domain (down-range/cross-range). As expected, the scattered field data in the image domain has some regions with high energy. The samples in the high-energy regions are used to obtain the initial guess for the ML estimator as well as for ML estimation. The ML estimator in the image domain is applied to both simulated and experimental scattered fields of some targets.

A method to design blended rolled edges for compact range reflectors

A method to design blended rolled edges for compact range reflectors with arbitrary rim shape is presented. The reflectors may be center-fed or offset-fed. The method leads to rolled edges with minimal surface discontinuities. It is shown that the reflectors designed using the prescribed method can be defined analytically using simple expressions. A procedure to obtain optimum rolled parameters is also presented. The procedure leads to blended rolled edges that minimize the diffracted field emanating from the junction between the paraboloid and the rolled edge surface while satisfying certain constraints regarding the reflector size and the minimum operating frequency of the system. >

SMI adaptive antenna arrays for weak interfering signals

The performance of adaptive antenna arrays in the presence of weak interfering signals (below noise level) is studied. It is shown that conventional adaptive arrays are unable to suppress such interfering signals. To overcome this problem, the feedback loops controlling the array weights are modified. In the modified feedback loops, the noise level in the feedback loops is reduced by reducing the correlation between the noise components of the two inputs to the loop correlator. Two techniques to decorrelate these noise components are discussed. It is shown that adaptive arrays with the modified feedback loops provide the desired interference suppression. An expression is given for the amount of noise decorrelation required to achieve a specified interference suppression.