Array processing is an area of study devoted to processing the signals received from an antenna array and extracting information of interest. It has played an important role in widespread applications like radar, sonar, and wireless communications. Numerous adaptive array processing algorithms have been reported in the literature in the last several decades. These algorithms, in a general view,...

This paper proposes a novel Bayesian solution to a difficult problem of joint detection and estimation of wideband sources impinging on a linear array of sensors in spatially colored noise with arbitrary covariance matrix. The wideband signals are approximated by an interpolation function and the signal samples. With the appropriate choices of prior distribution functions of the parameters, nui...

The constant modulus (CM) cost function is analyzed for array signal processing. The analysis includes arbitrary source types. It is shown that CM receivers have the signal space property except in two special cases. Local minima of CM cost function are completely characterized for the noiseless case. In the presence of measurement noise, the existence of CM local minima in the neighborhood of ...

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This article develops the mathematical models needed to describe the key issues in using an array of antennas for receiving spacecraft signals for DSN applications. The detrimental effects of nearby interfering sources, such as other spacecraft transmissions or natural radio sources within the array’s field of view, on signal-to noise ratio (SNR) are determined, atmospheric effects relevant to ...

Adaptive antenna arrays have been proposed to mitigate strong interference and multipath in Global Navigation Satellite Systems (GNSS) receivers. However, the high cost of an entire front-end and limited signal processing resources make large (or oversampled) antenna array a luxury for GNSS receivers. Therefore, a low cost adaptive array processing strategy by subarray selection is proposed in ...

Accurately sizing cracks has been a main objective of ultrasonic nondestructive evaluation for decades. Early sizing techniques based on echo amplitude have repeatedly been shown to be deficient. Diffraction techniques offer a significant improvement, but are also limited by pulse length and reliance on operator interpretation. In particular, Time-Of-Flight Diffraction is limited by pulse lengt...

This paper presents a novel array processing algorithm for noise reduction in a hands free car environment. The algorithm incorporates the spatial properties of the sound field in a car cabin and a constraint on allowable speech signal distortion. Our results indicate that the proposed algorithm gives substantial performance improvement of 15-20 dB in comparison with the conventional array proc...

a r t i c l e i n f o a b s t r a c t Array processing algorithms are used in many applications for source localization and signal waveform estimation. When the number of snapshots is small and/or the signal-to-noise ratio (SNR) is low, it becomes a challenge to discriminate closely-spaced sources. In this paper, two new array processing algorithms exploiting sparsity are proposed to overcome t...

y(t) = Ax(t) + e(t) (1) where y(t) ∈ Cm×1 and A = A(θ) ∈ Cm×nθ . It is assumed that: • Emitter signals x(t) are random. • Observation vectors {y(t)}t=1,2,... are i.i.d. circular Gaussian random variables with zero mean (, i.e. eiφZ has the same probability distribution as Z for all real φ, see for example [3]). • The emitter signal x(t) and the noise e(t) are uncorrelated which gives that R(θ, ...