Wideband Targets Research Articles

Wideband multitarget passive tracking based on belief propagation theory

In passive acoustic monitoring system, information is typically derived from radiated noise signals of targets distributed across multiple subbands. When targets are close in the node field of view, direct processing of the entire frequency band may lead to premature merging of detection results or masking of weaker targets due to differences in energy distribution among the target bands. This situation can degrade the performance of tracking algorithms because the downstream tracking processing cannot compensate for the loss of upstream measurements. This study proposes a novel wideband multitarget tracking algorithm based on belief propagation to address this challenge. Initially, a merged target model is established to simulate the mechanism of measurement generation from multiple targets. Based on this model, merged targets and each subband measurement form a cyclic association structure. This structure is processed using the loopy belief propagation algorithm to prevent the combinatorial explosion. A mixture of belief and mutual information entropy weight is established for each subband to fuse all posterior probability density functions, considering differences in subband energy distribution. Simulation and lake trial results demonstrate that this algorithm substantially improves the tracking capabilities of passive acoustic monitoring system for wideband targets, underscoring its practical application value.

DOA Estimation for Underwater Wideband Weak Targets Based on Coherent Signal Subspace and Compressed Sensing.

Direction of arrival (DOA) estimation is the basis for underwater target localization and tracking using towed line array sonar devices. A method of DOA estimation for underwater wideband weak targets based on coherent signal subspace (CSS) processing and compressed sensing (CS) theory is proposed. Under the CSS processing framework, wideband frequency focusing is accompanied by a two-sided correlation transformation, allowing the DOA of underwater wideband targets to be estimated based on the spatial sparsity of the targets and the compressed sensing reconstruction algorithm. Through analysis and processing of simulation data and marine trial data, it is shown that this method can accomplish the DOA estimation of underwater wideband weak targets. Results also show that this method can considerably improve the spatial spectrum of weak target signals, enhancing the ability to detect them. It can solve the problems of low directional resolution and unreliable weak-target detection in traditional beamforming technology. Compared with the conventional minimum variance distortionless response beamformers (MVDR), this method has many advantages, such as higher directional resolution, wider detection range, fewer required snapshots and more accurate detection for weak targets.

Accurate sound localization via head movements in listeners with precipitous high‐frequency hearing loss.

Information about sound source location in the vertical plane is available via the direction‐dependent filtering performed by the outer ears, but errors of localization such as front/rear reversals can occur when stimuli contain a limited range of frequencies or when high frequencies are inaudible due to hearing impairment. Information about front/rear sound source location is also available in the relationship between the rotation of the head and the resulting changes in interaural time and level differences. We have shown previously [Macpherson, J. Acoust. Soc. Am. 125, 2691(A) (2009)] that in normally hearing listeners, a minimum head movement angle (MHMA) of 5–10 deg is sufficient for accurate front/rear localization of low‐frequency (0.5–1 kHz) noise‐band targets. In the present study, we measured MHMAs for low‐frequency and wideband (0.5–16 kHz) targets in listeners with near‐normal low‐frequency thresholds but precipitous hearing loss above 1–2 kHz. Neither stimulus could be localized accurately by these listeners without head movement, but for both stimuli, MHMAs of 5–10 deg sufficed for accurate localization at a rotation velocity of 50 deg/s. MHMAs increased with increasing rotation velocity similarly to those of normally hearing listeners. The results suggest that listeners with normal hearing and with high‐frequency loss benefit similarly from dynamic localization cues. [Work supported by the NSF.]

Tracking Wide-Band Targets Having Significant Doppler Shift

A method is derived for passively locating wide-band targets (typically acoustic targets) which may be moving at speeds sufficient to produce significant Doppler shift. The method involves a relatively straightforward adaptation of standard beam forming techniques. It is shown that conventional beam forming techniques have less discrimination in the direction of motion of the sources, whereas the proposed technique exhibits no such degradation. The derivative and Hessian of the likelihood function are derived. These may be used for locating the maximum likelihood solution or for deriving a Gaussian approximation to the likelihood function for particle filtering applications. The expressions are applicable for subsonic and supersonic sources. The computation required for implementing a system based on the model is at present prohibitive

A model of auditory localization in noise using neural networks

Janko et al. [Binaural and Spatial Hearing in Real and Virtual Environments, edited by Gilkey and Anderson (Erlbaum, Hillsdale, NJ, 1996), pp. 557–570] used neural networks to describe auditory localization and found that data in quiet were insufficient to discriminate among models. To further constrain the models, localization in the presence of a spatially fixed masker is considered here. The wideband targets and maskers were filtered by head-related transfer functions, then by a gammatone filter bank. A model for binaural interaction similar to that of Lindemann [J. Acoust. Soc. Am. 80, 1608–1622 (1986)] was used to process the filter-bank outputs. The inhibited cross-correlation output of the binaural processor was sampled and used as input to a neural network (e.g., 24 correlation lags at each of 13 frequency channels for 312 input nodes). The network was trained using back propagation to estimate the target location in quiet, then tested on targets in noise at several values of signal-to-noise ratio (SNR). The network was also trained across several values of SNR. Results are compared to localization in noise by humans [Good and Gilkey, J. Acoust. Soc. Am. 99, 1108–1117 (1996)]. [Work supported by AFOSR F49620-95-1-0106 and the Ohio Board of Regents.]

Passive sonar detection and localization by matched velocity filtering

This paper presents a new bearings-only method of detecting and tracking low signal-to-noise ratio (SNR) wideband targets on a constant course and velocity trajectory. A track-before-detect strategy based on matched velocity filtering is adopted using spatial images constructed from a sequence of power bearing map (PBM) estimates accumulated during a track. To lower the threshold SNR for detection, a discrete bank of matched velocity filters integrates the PBM images over a range of hypothesized trajectories, such an approach eliminates the need to estimate the number of targets since signal detection is determined by comparing the output of each matched filter (MF) to a decision threshold. The distribution of the MF output is derived based on a single point target in diffuse noise assumption. Receiver operating characteristic curves show a definite detection gain under low SNR conditions for matched velocity filtering (track-before-detect) over detection from a single PBM.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>