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Array processing is widely used in sensing applications for estimating the locations and waveforms of the sources in a given field. In the absence of a large number of snapshots, which is the case in numerous practical applications, such as underwater array processing, it becomes challenging to estimate the source parameters accurately. This paper presents a nonparametric and hyperparameter, free-weighted, least squares-based iterative adaptive approach for amplitude and phase estimation (IAA-APES) in array processing. IAA-APES can work well with few snapshots (even one), uncorrelated, partially correlated, and coherent sources, and arbitrary array geometries. IAA-APES is extended to give sparse results via a model-order selection tool, the Bayesian information criterion (BIC). Moreover, it is shown that further improvements in resolution and accuracy can be achieved by applying the parametric relaxation-based cyclic approach (RELAX) to refine the IAA-APES&BIC estimates if desired. IAA-APES can also be applied to active sensing applications, including single-input single-output (SISO) radar/sonar range-Doppler imaging and multi-input single-output (MISO) channel estimation for communications. Simulation results are presented to evaluate the performance of IAA-APES for all of these applications, and IAA-APES is shown to outperform a number of existing approaches.

Broadband acoustic signals were transmitted during November 1994 from a 75-Hz source suspended near the depth of the sound-channel axis to a 700-m long vertical receiving array approximately 3250 km distant in the eastern North Pacific Ocean. The early part of the arrival pattern consists of raylike wave fronts that are resolvable, identifiable, and stable. The later part of the arrival pattern does not contain identifiable raylike arrivals, due to scattering from internal-wave-induced sound-speed fluctuations. The observed ray travel times differ from ray predictions based on the sound-speed field constructed using nearly concurrent temperature and salinity measurements by more than a priori variability estimates, suggesting that the equation used to compute sound speed requires refinement. The range-averaged ocean sound speed can be determined with an uncertainty of about 0.05 m/s from the observed ray travel times together with the time at which the near-axial acoustic reception ends, used as a surrogate for the group delay of adiabatic mode 1. The change in temperature over six days can be estimated with an uncertainty of about 0.006°C. The sensitivity of the travel times to ocean variability is concentrated near the ocean surface and at the corresponding conjugate depths, because all of the resolved ray arrivals have upper turning depths within a few hundred meters of the surface.

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During the Acoustic Engineering Test ͑AET͒ of the Acoustic Thermometry of Ocean Climate ͑ATOC͒ program, acoustic signals were transmitted from a broadband source with 75-Hz center frequency to a 700-m-long vertical array of 20 hydrophones at a distance of 3252 km; receptions occurred over a period of six days. Each received pulse showed early identifiable timefronts, followed by about 2 s of highly variable energy. For the identifiable timefronts, observations of travel-time variance, average pulse shape, and the probability density function ͑PDF͒ of intensity are presented, and calculations of internal-wave contributions to those fluctuations are compared to the observations. Individual timefronts have rms travel time fluctuations of 11 to 19 ms, with time scales of less than 2 h. The pulse time spreads are between 0 and 5.3 ms rms, which suggest that internal-wave-induced travel-time biases are of the same magnitude. The PDFs of intensity for individual ray arrivals are compared to log-normal and exponential distributions. The observed PDFs are closer to the log-normal distribution, and variances of log intensity are between (3.1 dB) 2 ͑with a scintillation index of 0.74͒ for late-arriving timefronts and (2.0 dB) 2 ͑with a scintillation index of 0.2͒ for the earliest timefronts. Fluctuations of the pulse termination time of the transmissions are observed to be 22 ms rms. The intensity PDF of nonidentified peaks in the pulse crescendo are closer to a log-normal distribution than an exponential distribution, but a Kolmogorov-Smirnov test rejects both distributions. The variance of the nonidentified peaks is (3.5 dB) 2 and the scintillation index is 0.92. As a group, the observations suggest that the propagation is on the border of the unsaturated and partially saturated regimes. After improving the specification of the ray weighting function, predictions of travel-time variance using the Garrett-Munk ͑GM͒ internal-wave spectrum at one-half the reference energy are in good agreement with the observations, and the one-half GM energy level compares well with XBT data taken along the transmission path. Predictions of pulse spread and wave propagation regime are in strong disagreement with the observations. Pulse time spread estimates are nearly two orders of magnitude too large, and ⌳-⌽ methods for predicting the wave propagation regime predict full saturation.