Waveform design with time and frequency constraints for optimal detection of elastic objects

Hamschin, Brandon; Loughlin, Patrick J.

doi:10.1117/12.884134

Cited by 4 publications

(4 citation statements)

References 40 publications

(51 reference statements)

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“…(6) by allowing it to be defined by M different target/environment models. 22 The source of these models can then be any combination of a priori knowledge, estimates based on in situ techniques, or responses to queries of a target response database.…”

Section: Discussionmentioning

confidence: 99%

“…This trait is encountered repeatedly in approaches to designing optimal signals for detection 6,23,24 or classification. 22,25 In summary, if one is able to characterize the spectral properties of the target and the environment, the probability of detection is maximized by transmitting a signal whose magnitude spectrum is given by B opt ðxÞ. Note that optimal detection performance is independent of the spectral phase of the transmit waveform, and hence there is an unlimited number of possible time-domain waveforms that are "optimal" in this regard-an observation that motivates the developments of Sec.…”

Section: Background: Optimizing Spectral Magnitudementioning

confidence: 92%

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Time and frequency constrained sonar signal design for optimal detection of elastic objects

Hamschin

Loughlin

2013

The Journal of the Acoustical Society of America

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In this paper, the task of model-based transmit signal design for optimizing detection is considered. Building on past work that designs the spectral magnitude for optimizing detection, two methods for synthesizing minimum duration signals with this spectral magnitude are developed. The methods are applied to the design of signals that are optimal for detecting elastic objects in the presence of additive noise and self-noise. Elastic objects are modeled as linear time-invariant systems with known impulse responses, while additive noise (e.g., ocean noise or receiver noise) and acoustic self-noise (e.g., reverberation or clutter) are modeled as stationary Gaussian random processes with known power spectral densities. The first approach finds the waveform that preserves the optimal spectral magnitude while achieving the minimum temporal duration. The second approach yields a finite-length time-domain sequence by maximizing temporal energy concentration, subject to the constraint that the spectral magnitude is close (in a least-squares sense) to the optimal spectral magnitude. The two approaches are then connected analytically, showing the former is a limiting case of the latter. Simulation examples that illustrate the theory are accompanied by discussions that address practical applicability and how one might satisfy the need for target and environmental models in the real-world.

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Section: Discussionmentioning

confidence: 99%

Section: Background: Optimizing Spectral Magnitudementioning

confidence: 92%

Time and frequency constrained sonar signal design for optimal detection of elastic objects

Hamschin

Loughlin

2013

The Journal of the Acoustical Society of America

Self Cite

View full text Add to dashboard Cite

show abstract

“…Thus, the spectral phase is very critical to the generation of transmit waveform. The spectral phase optimisation design can be referred to [30]. In practice, a waveform with short duration can be transmitted more frequently.…”

Section: Optimisation Of Waveform Designmentioning

confidence: 99%

“…For convenience, the transmitted waveform