The sonar equations: definitions, dimensions and units of individual terms

For many active sonar problems there exists an optimum frequency for detection. In this paper, the optimum frequency is defined as the frequency which maximizes the signal excess of a monostatic active sonar system in shallow water. The optimum frequency is a function of range and can be calculated using the sonar equation which includes several frequency dependent terms. Active sonar in shallow water may be reverberation limited rather than noise limited, which impacts the optimum frequency. Standard Lambert bottom interface scattering strength models are frequency independent, however more accurate data-derived bottom backscatter strength models are frequency dependent. The bottom scattering strength model choice is important for determining the optimum frequency. Finally, volume reverberation due to biological activity (scattering from fish) has a complicated frequency dependence, which changes the optimum frequency. In addition to calculating the optimum frequencies for these cases, this work also quantifies the performance degradation caused by a suboptimum frequency selection.

A model is proposed for simulating the group dynamics and acoustic echoes of aggregate, discrete biologics in midfrequency (2–5 kHz) active undersea sonar. Using a Lagrangian description, group behavior is modeled by a set of Newtonian forces and stochastic perturbations on a collection of point masses. Interactions comprise a grouping force, which gives a characteristic separation distance, and an arrayal force, which tends to align the velocities of the group’s constituents. The group dynamics is characterized in terms of their statistical and asymptotic properties and studied as a function of the model parameters. Several models for the acoustic response are considered and studied for both individual and aggregate response. Finally, the resulting synthetic echoes are compared against those of actual biologics measured on a midfrequency active sonar system. The synthetic echoes are found to reproduce well both the qualitative characteristics of measured biologics and the resulting tracking and classification features found in a typical active sonar signal and information processing chain.

The time and energetic costs of behavioral responses to incidental and experimental sonar exposures, as well as control stimuli, were quantified using hidden state analysis of time series of acoustic and movement data recorded by tags (DTAG) attached to 12 sperm whales (Physeter macrocephalus) using suction cups. Behavioral state transition modeling showed that tagged whales switched to a non-foraging, non-resting state during both experimental transmissions of low-frequency active sonar from an approaching vessel (LFAS; 1-2 kHz, source level 214 dB re 1 µPa m, four tag records) and playbacks of potential predator (killer whale, Orcinus orca) sounds broadcast at naturally occurring sound levels as a positive control from a drifting boat (five tag records). Time spent in foraging states and the probability of prey capture attempts were reduced during these two types of exposures with little change in overall locomotion activity, suggesting an effect on energy intake with no immediate compensation. Whales switched to the active non-foraging state over received sound pressure levels of 131-165 dB re 1 µPa during LFAS exposure. In contrast, no changes in foraging behavior were detected in response to experimental negative controls (no-sonar ship approach or noise control playback) or to experimental medium-frequency active sonar exposures (MFAS; 6-7 kHz, source level 199 re 1 µPa m, received sound pressure level [SPL] = 73-158 dB re 1 µPa). Similarly, there was no reduction in foraging effort for three whales exposed to incidental, unidentified 4.7-5.1 kHz sonar signals received at lower levels (SPL = 89-133 dB re 1 µPa). These results demonstrate that similar to predation risk, exposure to sonar can affect functional behaviors, and indicate that increased perception of risk with higher source level or lower frequency may modulate how sperm whales respond to anthropogenic sound.

Marine mammals use sound for critical life functions through passive listening and, in some species, active sonar. Major recent advances have been made in understanding what sounds they make, how they hear, and how noise affects their hearing, behavior, and physiology. While data are lacking for whole groups, notably baleen whales, direct hearing measurements are available for most taxa. Some species, such as odontocete cetaceans, hear extremely broad frequency ranges, well into ultrasonic biosonar frequencies. Pinnipeds have more limited frequency ranges but are adapted for aerial and underwater hearing. Indirect data suggest whales use and are more sensitive to low frequencies. For most species, quite high received sound levels are required to temporarily or permanently affect hearing. Direct experimental measurements of behavioral responses have revealed strong species and context dependencies, with factors such as proximity, novelty, and spatial relationships influencing response probability as well as relative loudness. For active surveillance sonar systems operating in the 30-200 kHz range, whales and otariid pinnipeds are of much less concern in terms of audibility and potential behavioral disturbance than phocid pinniped and odontocete cetaceans, notably porpoises. Hearing loss or other injuries from such systems are quite unlikely in almost all practical scenarios.

Mulloway (Argyrosomus japonicus) in Mosman Bay, Western Australia produce three call categories associated with spawning behavior. The determination of call source levels and their contribution to overall recorded sound pressure levels is a significant step towards estimating numbers of calling fish within the detection range of a hydrophone. The source levels and ambient noise also provide significant information on the impacts anthropogenic activity may have on the detection of A. japonicus calls. An array of four hydrophones was deployed to record and locate individual fish from call arrival-time differences. Successive A. japonicus calls produced samples at various ranges between 1 and 100 m from one of the array hydrophones. The three-dimensional localization of calls, together with removal of ambient noise, allowed the determination of source levels for each call category using observed trends in propagation losses and interference. Mean source levels (at 1 m from the hydrophone) of the three call categories were calculated as 163 ± 16 dB re 1 μPa for Category 1 calls (short call of 2-5 pulses); 172 ± 4 dB re 1 μPa for Category 2 calls (long calls of 11-32 pulses); and 157 ± 5 dB re 1 μPa for Category 3 calls (series of successive calls of 1-4 pulses, increasing in call rate).

The statistics of reverberation in active sonar are characterized by non-Rayleigh amplitudes in the normalized matched filter output. Unaccounted for, this property can lead to high false alarm rates in fixed-threshold detectors. A new approach to modeling threshold-crossing statistics based on extreme value theory is proposed which uses the generalized Pareto distribution as the unique, asymptotic model of the tail distribution, valid at large thresholds. Methods of parameter estimation are discussed and applied to active sonar reverberation collected on a hull-mounted sonar system. The statistics of reverberation in active sonar are found to generally have a power-law behavior in the tails with a shape parameter that is persistent in time and bandwidth dependent. The threshold needed for accurate parameter estimation is generally found to be well below that of typical fixed-threshold detectors.

Underwater multi-targets tracking has always been a difficult problem in active sonar tracking systems. In order to estimate the parameters of time-varying multi-targets moving in underwater environments, based on the Bayesian filtering framework, the Random Finite Set (RFS) is introduced to multi-targets tracking, which not only avoids the problem of data association in multi-targets tracking, but also realizes the estimation of the target number and their states simultaneously. Usually, the conventional Probability Hypothesis Density (PHD) and Cardinalized Probability Hypothesis Density (CPHD) algorithms assume that the detection probability is known as a priori, which is not suitable in many applications. Some methods have been proposed to estimate the detection probability, but most assume that it is constant both in time and surveillance region. In this paper, we model the detection probability through the active sonar equation. When fixed the false detection probability, we can get the analytic expression for the detection probability, which is related to target position. In addition, this novel detection probability is used in PHD and CPHD algorithms and applied to underwater active sonar tracking systems. Also, we use the adaptive ellipse gate strategy to reduce the computational load in PHD and CPHD algorithms. Under the linear Gaussian assumption, the proposed detection probability is illustrated in both Gaussian Mixture Probability Hypothesis Density (GM-PHD) and Gaussian Mixture Cardinalized Probability Hypothesis Density (GM-CPHD), respectively. Simulation results show that the proposed Pd-GM-PHD and Pd-GM-CPHD algorithms are more realistic and accuratein underwater active sonar tracking systems.

Active sonar systems are used in the detection and localization of underwater targets. While traditional approaches use pulsed active sonar (PAS) to transmit short bursts, high duty cycle (HDC) sonar systems have been the focus of recent research and can overcome the shortcomings of PAS. Since HDC sonar systems transmit a long pulse train waveform, we must address sub-pulse interference issues, which requires multiple orthogonal sub-pulses and generalized sinusoidal frequency modulated (GSFM) pulses are suitable for this purpose. Unfortunately, conventional GSFM pulse train design methods do not generate an adequate number of orthogonal sub-pulses. Therefore, we propose an improved GSFM pulse train waveform design approach for overcoming the limitations of these conventional methods. The proposed method is organized into two parts, the first focused on the assessment of the auto-correlation, and the second focused on the optimizing the orthogonality between sub-pulses. Cost function is also carefully designed for this purpose. From simulation experiments, we found that the proposed method was able to produce 30 orthogonal sub-pulses and an optimized waveform that demonstrated better detection performance than conventional waveforms under most conditions. We also verified the performance of the proposed method via actual sea experiments, with analysis showing superior performance matching that of simulations. An analysis on the bandwidth parameter K is also conducted and it is found K = 1.25 to be the best option.

본 논문은 반향음과 투과음을 감소시키기 위한 평판형 음향재료의 성능평가 장치를 제작하고 측정시스템을 구성하며 표준표적을 이용한 검증을 통해 신뢰성을 확보하는 데 목적이 있다. 반향음감소와 투과손실 측정은 신호간섭이 없도록 대형수조에서 실시되는 것이 일반적이지만, 본 논문에서는 신호간섭을 고려해야 하는 소형수조에서 최저 30 kHz까지 측정이 가능한 측정시스템을 구성하였다. 이를 위해 신호모의를 통해 신호간섭이 없는 최적의 기하학적 배치를 도출하였으며, 획득한 신호를 시간영역과 주파수영역의 총 네 가지 방법으로 ER과 TL을 도출하는 신호처리 알고리즘을 확립하였다. 마지막으로 대형수조에서의 전파손실 실측실험을 통해 측정시스템을 보정하고 알루미늄 판과 스티로폼을 표준표적으로 사용한 측정결과를 Brekhovskikh Layer Model과 비교하여 측정시스템 검증을 수행하였다. Since the detection probability is critically dependent on the target strength (TS) in active sonar and on the radiated noise level (RNL) in passive sonar, the acoustic materials for echo reduction (ER) and transmission loss (TL) are widely used for the stealth of underwater targets. In this paper, a measurement system based on the small water tank, for the frequency range of greater than 30 kHz, is developed and verified using reference targets. In order to design the water tank and the geometry of test samples, a program is developed to calculate the arrival time of interfering signals due to the reflection from water tank walls and also due to the diffraction from the edge of the test samples. Considering all the interfering signals, an optimal experimental configuration for water tank and test samples is designed and used throughout the experiment. Next, the signal processing algorithms to estimate ER and TL are developed based on the measured propagation loss reflecting the geometric spreading characteristics of the transducer. Finally, a set of reference targets such as aluminium plate and perfectly reflecting plate are used in a small water tank to verify the developed measurement system.

Field recordings of harbour porpoises (Phocoena phocoena) were made in the inner Danish waters with a vertical array of three or four hydrophones. The back-calculated source level ranged from 178 to 205 dB re 1 muPa pp @ 1 m with a mean source level of 191 dB re 1 muPa pp @ 1 m. The maximum source level was more than 30 dB above what has been measured from captive animals, while the spectral and temporal properties were comparable. Calculations based on the sonar equation indicate that harbour porpoises, using these high click intensities, should be capable of detecting fish and nets and should be detectable by porpoise detectors over significantly larger distances than had previously been assumed. Harbour porpoises in this study preferred a relatively constant inter-click interval of about 60 ms, but intervals up to 200 ms and down to 30 ms were also recorded.

In this paper, the author discusses a Broadband Bionic Sonar Sensor System and a signal processing technique for detection and identification of underwater targets. This bionic sonar system with the resonance detection technique for detection and identification of underwater objects appears to mimic a dolphin's sensory system. The dolphin's sonar system transmits a very short broadband pulse. It detects and classifies a target by processing the modulation of the echo's (back scattering) broadband spectrum. This spectral modulation is directly related to the target's natural resonance. Using the G-Transform technique, the author has successfully showed that target resonance exists and it is unique to target size, shape, structure and material composition. Furthermore, this natural resonance exists in both (active sonar) acoustic echoes, back scattering and (passive sonar) acoustic scattering in acoustic noise background. Using trained neural networks, these targets' resonances/signatures can be correctly identified for the respective targets. It is conceivable that a broadband radar system, similar to a dolphin's sonar system, can be developed for targets and subsurface targets.© (1999) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

The core problem for networked systems for underwater surveillance revolves around the requirement to blend information from different sensors and platforms into a common operating picture. Data fusion of disparate data types can be problematic given the variety of potential surveillance systems in the network. Active and passive sonar in particular provide different data types with different accuracies. The acoustic environment is highly stochastic and errors are prevalent that can be promulgated throughout the system. An evolutionary algorithm approach for fusing active and passive sonar contact information is used to explore the issue of robustness when large contact errors prevail from multiple platforms. The algorithm may have the ability to recover from erroneous input at the expense of lower track accuracy. This may have a significant utility as an operator aid for construction of the global picture of fused active and passive data. A multitude of erroneous sources can still result in higher overall track errors and further research is required; however, the evolutionary approach may still provide significant benefit

Fields of distributed passive and multistatic active sonar sensors provide surveillance capabilities against quiet submarine threats in Anti-Submarine Warfare (ASW) scenarios. The joint cooperative use of passive and active sonar offers synergistic and complimentary acoustic performance as well as operational advantages. However, a significant challenge of heterogeneous, multi-sensor systems is the successful fusion of information from the various sensors to enable robust target detection, classification, localization, and tracking. This paper describes the formation of a passive acoustic track that may be used to cue an active multistatic acoustic tracking system. A cue from a passive acoustic track reduces the false track rate in the active tracker by focusing the search area and selectively initiating active tracks. The passive track is assumed to originate from a fixed passive acoustic horizontal line array (HLA) which is unable to determine target range or resolve the familiar left-right ambiguity. However, passive systems can predict Closest-Point-of-Approach (CPA) events. For each CPA event, a cue can be forwarded to the active system for multistatic active track initiation. This paper presents a minimal parametric representation for a passive acoustic track. It also describes an algorithm for obtaining initial estimates of parameters that can be used to initiate the passive track more effectively. A performance evaluation is given. This paper also describes the conversion of the passive track to pseudo-coordinates that are convenient for use with a multistatic tracking system. Lastly, a method for measuring passive track quality is described which determines if track quality is sufficient to justify cueing the active multistatic system.

Active sonar systems can provide good target detection potential but are limited in shallow water environments by the high level of reverberation produced by the interaction between the acoustic signal and the ocean bottom. The nature of the reverberation is highly variable and depends critically on the ocean and seabed properties, which are typically poorly known. This has motivated interest in techniques that are invariant to the environment. In passive sonar, a scalar parameter termed the waveguide invariant, has been introduced to describe the slope of striations observed in lofargrams. In this work, an invariant for active sonar is introduced. This active invariant is shown to be present in the time-frequency structure observed in sonar data from the Malta Plateau, and the structure agrees with results produced from normal mode simulations. The application of this feature in active tracking algorithms is discussed.

This is a collection of articles written by members of the Underwater Acoustic Signal Processing (UASP) Technical Committee. The first article, by D. W. Tufts, deals with the history of UASP prior to 1980. In this period, initial mathematical models were developed and the first experimental investigations of underwater acoustic propagation were performed. It was also recognized during this time that there are many similarities between radar and sonar signal processing. The article by J.P. Ianniello deals with research in passive and active sonar from 1980 to the present. Work in this period included experimental verification of algorithms that had been developed in the 1960s and 1970s (e.g. for adaptive beamforming), as well as the development of new approaches, which include acoustic propagation modeling in the design of signal processing algorithms. Such processing is referred to as matched field processing. A common task in passive sonar systems is to estimate the difference in times at which different sensors receive the same signal. Time-delay estimation is a first stage that feeds into subsequent processing blocks. I. Lourtie provides a concise review of work in this field. The article by J.C. Preisig deals with underwater acoustic communications. The underwater channel has several features that make reliable communication a challenging problem. Nevertheless, progress is being made by combining results from ocean acoustic modeling, communication theory, and signal processing. The final article, by J.M.F. Moura, deals with the future of signal processing in the ocean. In addition to considering advances in detection and localization, he deals with new applications such as acoustic tomography, physical oceanography, and synthetic aperture sonar.