1.

Introduction

For almost a century, the United States Navy has relied on acoustic sensors to map, detect threats or obstacles, and transmit information. However, with limited resources available and the desire to limit exposure to equipment and crew, alternative methods to conduct operations in mine warfare, antisubmarine warfare, and naval special warfare were developed.¹ One such development is the use of electro-optical identification (EOID) sensors in conjunction with acoustic sensors to detect, classify, localize, and identify sea mines.² EOID systems have become integral components in mine countermeasures operations and support mine identification missions by imaging objects that reside in water volume (moored and drifting mines) or on seabed (bottom and close-tethered mines).³ With the sensor development, the U.S. Navy has developed the electro-optical detection simulator (EODES)⁴ to identify quality of optical detection. The EODES is included in the Oceanographic and Atmospheric Master Library. It has a number of applications, such as detecting harmful objects beneath the surface or on the bottom of the ocean floor, tracking moving underwater objects, and communicating with either stationary or moving objects and vessels under the surface (Fig. 1).

Fig. 1

Front and side views of a synchronous series EOID system (after Ref. 3).

Tropical storms, especially typhoons/hurricanes, generate strong surface wind stress that enhances the currents, waves, and turbulences, and in turn changes the absorption and scattering of the water and constituents within, such as particles of various origins, including algal cells, detritus, sediments, plankton, and even bubbles near the surface. This increases significantly the beam attenuation coefficient and in turn reduces the quality of EOID.⁵ Typhoons often hit the western North Pacific Ocean.⁶ However, little attention has been paid to the effects of typhoon/hurricane’s passage on optical detection, despite evidence suggesting that the strong winds significantly affect underwater IOPs such as beam attenuation coefficient and in turn the quality of EOID.⁷

To fill the gap, we choose a typhoon influenced area of high ocean transparency with low seasonal optical variability. The Secchi disk depth (SDD) is a key index of water transparency. Figure 2 shows the global climatological annual mean SDD and its absolute seasonal amplitude (maximum − minimum) derived from the satellite observations by the sea-viewing wide field-of-view sensor (SeaWiFS).⁸ The area (124°E–134°E and 15°N–27°N), bounded by white lines in Fig. 2, is characterized as high transparency with low seasonal variability. Since seasonal and spatial differences in phytoplankton concentrations are low in this area, it is a perfect place to investigate the effect of tropical storms on the optical detection.

Fig. 2

Global distributions of (a) the climatological annual mean SDD (m) and (b) absolute seasonal amplitude (maximum − minimum) of the climatological monthly mean SDD (m) derived from the SeaWiFS data over the period of September 1997 to November 2010 (from Ref. 8). Note that the area (124°E–134°E and 15°N–27°N) bounded by the white lines shows high transparency with low variability.

In 2012, a tropical disturbance formed south–southeast of Pohnpei on June 7 and was upgraded to a tropical depression on June 10. The system later intensified in favorable conditions and reached typhoon intensity (i.e., typhoon Guchol) on June 15. It reached super typhoon status on June 16 and 17, before making landfall over Japan as a typhoon on June 19 (Fig. 3). Guchol brought heavy rain and strong winds in the western Pacific Ocean near Japan on June 19 and 20. Investigation of EOID quality after typhoon passage in comparison to that without typhoon activities shows the typhoon effect. The IOPs were measured from Seagliders of the Naval Oceanographic Office (NAVOCEANO) during two different periods: (a) June 25 to 30, 2012, which is 7 days after super typhoon Guchol’s passage and (b) January 9 to February 28, 2014, with no typhoon activities. The Navy’s EODES is integrated with the two sets of IOPs and the quality of optical detection is identified. The reminder of this paper is outlined as follows. Section 2 describes observed IOPs with and without typhoon passage. Section 3 describes the Navy’s EODES. Section 4 shows the super typhoon Guchol’s effect. Section 5 presents the conclusions.

Fig. 3

Geography of the western North Pacific Ocean and track of super typhoon Guchol-2012 with strength. The integers in circles indicate the dates in June 2012. The colors in circles represent the strength of Guchol.

2.

IOPs with and without Typhoon Passage

The glider is a remote operator programmed to perform a series of downward and upward tracks while collecting various oceanographic parameter data using various installed sensor packages. It can position itself at the ocean surface with a 45-deg downward angle to present the antenna array skyward to facilitate two-way satellite communications. The NAVOCEANO Seaglider has the Seabird Electronics SBE 41 CP CTD sensor (hydrographic measurement) and WET Lab’s beam attenuation meter (optical measurement).⁹

Profile data of three Seagliders were obtained from the NAVOCEANO. Among them, two Seagliders (NG226 and NG232) were deployed from a survey ship in the area where super typhoon Guchol passing by 7 days ago. They were 15 min and 223 m apart: UTC 03:19, June 25, 2012 at (25°30′20″N and 131°59′51″E) for NG226 [blue trajectory in Figs. 4(a) and 4(b)] and UTC 03:34, June 25, 2012, at (25°30′27″N and 131°59′55″E) for NG232 [red trajectory in Figs. 4(a) and 4(b)]. The two Seagliders took very different trajectories despite they were very close (only 223 m apart) initially with NG226 drifting southwestward and then southward and NG232 drifting southeastward and then northeastward. On June 30, 2012, NG226 was located at (24°59′27″N and 131°59′26″E) on UTC 17:24; however, NG232 was located at (25°34′50″N and 132°10′20″E) on UTC 17:51. Such strong bifurcation of ocean currents was generated at the wake of super typhoon Guchol. The third Seaglider (NG270) was underwater during January 6 to February 28, 2014, without any typhoon activities [magenta trajectory in Fig. 4(a)]. The beam attenuation coefficient $c$ (470 nm) measured by NG 226 (59 profiles) and NG 232 (86 profiles) during June 25 to 30, 2012, after super typhoon Guchol passage [Figs. 5(a) and 5(b)] is large with horizontally averaged values (red solid profiles) generally $>0.8{\mathrm{m}}^{-1}$. The beam attenuation coefficient $c$ (470 nm) measured by NG 270 (825 profiles) during January 6 to February 28, 2014, with no typhoon activity (Fig. 6) is much smaller with horizontally averaged values $<0.05{\mathrm{m}}^{-1}$.

Fig. 4

Tracks of (a) NAVOCEANO Seagliders NG270 during January 9 to February 28, 2014 (red), without typhoon activity, as well as Seagliders (NG226 and NG232) during June 25 to 30, 2012 (blue), after super typhoon Guchol’s passage and (b) zoomed-in view of (NG226 and NG232).

Fig. 5

Beam attenuation coefficient $c$ (470 nm) profiles collected from (a) glider NG 226 (59 profiles) and (b) glider NG 232 (86 profiles) June 25 to 30, 2012 (after super typhoon Guchol passage). The red solid profiles are horizontally averaged values generally $>0.8{\mathrm{m}}^{-1}$.

Fig. 6

Beam attenuation coefficient $c$ (470 nm) profiles collected from glider NG 270 (825 profiles) January 6 to February 28, 2014, with no typhoon activity. The red solid profiles are horizontally averaged values generally $<0.05{\mathrm{m}}^{-1}$.

3.

Navy’s EODES

The EODES is the Navy’s standard model for identification of quality in optical detection. It simulates the propagation of a narrow, highly collimated beam of light (e.g., laser) through a scattering and absorbing seawater where the IOPs vary in the direction of the beam axis. It provides tactical performance prediction for the laser line scan (LLS) sensor of several AQS-24a systems for mine countermeasure in the fleet.^4,10 The simulator consists of four modules: (a) utility, (b) radiative transfer, (c) EOID sensors and systems, and (d) environmental state.

3.3.

EOID Sensors and Systems

For underwater EOID applications, a highly collimated, monochromatic laser light source is typically used. Diffuse solar illumination of the optical medium and the scene also tends to be present. Loosely speaking, radiation emanating or reflecting from the scene is beneficial to the imaging process, whereas energy added to the path from any other source is detrimental. Let the target and sensor be at depths $z_D$ and $z_S$. The laser source and collector are separated by a distance $d_{SC}$. When the source and collector are separated, the collector aperture (or laser aperture) must by tilted at an angle ${\theta }_C$ so that the laser beam axis and collector line-of-sight intersect near the target scene depth. The source–collector separation $d_{SC}$ and the collector angle ${\theta }_C$ determine the relative along-track offset $\mu$ (see Fig. 7)

Eq. (4)

$$\mu (z)=d_{SC}-(z-z_S)\tan {\theta }_C$$

between the laser beam axis and collector line-of-sight at depth $z$. Ideally,

Eq. (5)

$$\mu (z_D)=0$$

such that the source and collector axes intersect at the target plane. The laser aperture half-angle ${\alpha }_s$ characterizes the axisymmetric angular variation in emitted light for the narrow, collimated laser beam, and it corresponds to the angular variation of emitted light in the case of a fan beam. Note that the fan beam illuminates the entire cross-track field of view instantaneously.

Fig. 7

Illustration of an EODES system (from Ref. 10).

In the LLS sensor, the relative edge response (measuring the blurring and contrast loss of image) depends on the optical transfer function of the system. A simplified rating scale is used to measure relative performance, which is based on a predefined scale using a simple traffic light decision aid, i.e., image quality (IQ) of red (no go), yellow (questionable), and green (go). Such a rating is a function of ground sampled distance (GSD) and signal-to-noise ratio (SNR). The GSD in the LLS sensor measures the image resolution. In the fan-type beam, the along-track (${\mathrm{GSD}}_a$) and cross-track (${\mathrm{GSD}}_c$) values are given by⁴

Eq. (6)

$${\mathrm{GSD}}_a=15U/\mathrm{\Omega },{\mathrm{GSD}}_c=2(z_D-z_S)\tan ({\theta }_C)/N,$$

where $U$ is the platform speed ($\mathrm{m}{\mathrm{s}}^{-1}$), $\mathrm{\Omega }$ is the spindle rotation rate (rpm), and $N$ is the number of pixels in the cross-track direction across entire swath width (Table 1).

Table 1

EOID system parameters and operational settings for the LLS system (from Ref. 4).

Parameter	Unit	Value
Laser power ($P$)	W	0.5
Laser aperture	Radian	0.001
Along-track collector aperture	Radian	0.002
Cross-track collector aperture	Radian	0.002
Cross-track angular field of view ($2{\theta }_C$)	Degree	70.0
Number of cross-track pixels ($N$)	—	1024
Collector area	${\mathrm{m}}^2$	0.002
Source–collectors separation distance	M	0.4
Spindle rotation rate ($\mathrm{\Omega }$)	RPM	4000.0
Photomultiplier tube efficiency	—	0.11
Source transmission coefficient	—	0.5
Collector transmission coefficient	—	0.5
Platform speed ($U$)	$\mathrm{m}{\mathrm{s}}^{-1}$	4.0
Platform (sensor) depth ($z_S$)	M	193.0
Water or target depth ($z_D$)	M	200.0

4.

Effect of Super Typhoon Guchol

Detection quality of EOID systems depends on the environment. If waters are highly turbid or have a significant amount of absorbent materials suspended in the water column, the effectiveness of these sensors is low due to the degradation of the optical signal. The EODES needs environmental input such as vertical profiles of scattering coefficient $b(z)$ (${\mathrm{m}}^{-1}$), beam attenuation coefficient $c(z)$ (${\mathrm{m}}^{-1}$), volume back scattering phase function ${\beta }_{\pi }(z)$ (${\mathrm{m}}^{-1}{\mathrm{str}}^{-1}$), ambient (solar) light such as solar irradiance and altitude at the ocean surface, and the corresponding diffuse attenuation coefficient $K_d(z)$ (${\mathrm{m}}^{-1}$). The beam attenuation coefficient $c(z)$ is the only IOP observed from the Seaglider. The other environmental parameters are calculated. With the albedo $\omega$, we compute the volume absorption coefficient $a(z)$ and scattering coefficient $b(z)$ using (2). With $a(z)$ and $b(z)$, we calculate the diffuse attenuation coefficient $K_d(z)$ using Eq. (10).

The cross sections of the beam attenuation coefficient $c(z)$ during January 6 to February 28, 2014, without typhoon activity along the track of the NAVOCEANO Seaglider NG270 [Fig. 8(a)] show small values $c<0.05{\mathrm{m}}^{-1}$ (${10}^{-1.3}$ to 0.05 and ${10}^{-1.9}$ to 0.013). The corresponding $D_{\max }$ simulated by the EODES usually fluctuates between 17 and 19 m with two lower spikes of 13.7 and 15.4 m [Fig. 8(b)], which indicates the feasibility of using EOID for detection.

Fig. 8

Cross section of observed volume attenuation coefficient $c(z)$ along the tracks of NAVOCEANO Seaglider NG270 during January 6 to February 28, 2014, (red) (a) without typhoon activity and (b) simulated maximum detectable depth by EODES ($D_{\max }$). The horizontal axis shows the glider’s location along the magenta-colored track in Fig. 5(a) with station-1 located at (19°36′32′N and 124°58′56″E) on 05:01 UTC, January 09, 2014, and station-825 (19°59′27″N and 127°34′05″E) at 17:26 UTC, February 28, 2014. It is noted that there was no typhoon passing by during that period.

On the other hand, the cross sections of the beam attenuation coefficient $c(z)$ during January 25 to 30, 2012, after super typhoon Guchol’s passage is larger than $0.74{\mathrm{m}}^{-1}$ (${10}^{-0.13}$ to 0.74) along the tracks of the NAVOCEANO Seaglider NG226 [Fig. 9(a)] and $0.79{\mathrm{m}}^{-1}$ (${10}^{-0.1}$ to 0.79) along the NAVOCEANO Seaglider NG232 [Fig. 9(b)]. The corresponding $D_{\max }$ simulated by the EODES usually fluctuates between 3.4 and 4.6 m along NG226 [Fig. 9(c)] and 2.3 and 4.5 m along NG232 [Fig. 9(d)]. This indicates that the super typhoon Guchol l reduced the maximum detectable depth by about 15 m after 7 to 13 days passage.

Fig. 9

Cross section of observed volume attenuation coefficient $c(z)$ along the tracks of NAVOCEANO Seaglider (a) NG226 and (b) NG232 (January 25 to 30, 2012) (c), (d) 7 days after super typhoon Guchol’s passage and simulated maximum detectable depth by EODES ($D_{\max }$). The horizontal axis in (c) shows the glider’s location along the blue-colored track in Fig. 4(b) with station-1 located at (25°30′20″N and 131°59′51″E) on UTC 03:19, June 25, 2012, and station-59 (24°59′27″N and 131°59′26″E) at UTC 17:24, June 30, 2012. The horizontal axis in (d) shows the glider’s location along the red-colored track in Fig. 4(b) with station-1 located at (25°30′27″N and 131°59′55″E) on UTC 03:34, June 25, 2012, and station-86 located at (25°34′50″N and 132°10′20″E) on UTC 17:51, June 30, 2012. It is noted that the super typhoon Guchol moved out the area on June 18, 2012.

5.

Conclusion

This study identifies the typhoon effects on EOID in the western North Pacific Ocean using the Navy’s EODES with the data collected by three NAVOCEANO Seagliders. The beam attenuation coefficient $c$ (470 nm) was measured during June 25 to 30, 2012, after super typhoon Guchol’s passage and from January 6 to February 28, 2014, with no typhoon activity. Huge difference was found in the horizontally averaged $c$ with $>0.74{\mathrm{m}}^{-1}$ during typhoon Guchol’s passage and with much smaller values $<0.05{\mathrm{m}}^{-1}$ without typhoon activity. The Navy’s EODES is integrated using observed IOPs from the NAVOCANO Seagliders with and without the influence of typhoon. The simulated results show that the super typhoon Gochol largely reduced the maximum detectable depth of EOID by about 15 m in comparison to without typhoon activity. We note that the results only show the strong typhoon effect through comparison between NG226, NG232, and NG270 during the two periods: June 25 to 30, 2012, and January 6 to February 28, 2014. These two short durations are not enough to conclude and affirm the feasibility of using EOID in the western North Pacific Ocean without typhoon passage because it is well known that the IOPs of the underwater channel can be easily affected by phenomena such as wind, surface waves, optical turbulences, and water currents. It will be investigated in future studies using more complete dataset.