HiCASS Target Tracking Sensor Study

for 

Oceaneering Technology Corporation 

Upper Marlboro, MD 

Richard J. Norcross 

Intelligent Systems Division 

National Institute of Standards and Technology 

Gaithersburg, MD 20899-8230

NISTIR 7220

2005
HiCASS Target Tracking Sensor Study 

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Disclaimer

No approval or endorsement of any commercial product by the National Institute of 

Standards and Technology is intended or implied. Certain commercial equipment, 

instruments, or materials are identified in this report to facilitate understanding. Such 

identification does not imply a recommendation or endorsement by the National Institute 

of Standards and Technology, nor does it imply that the materials or equipment identified 

are necessarily the best available for the purpose. 

Copyright

This publication was prepared by United States Government employees as part of their 

official duties and is, therefore, a work of the U.S. Government and not subject to 

copyright.
HiCASS Target Tracking Sensor Study 

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Abstract 

The High Capacity Alongside Sea base Sustainment (HiCASS) program intends to 

generate substantial improvements in skin-to-skin at-sea replenishment. HiCASS requires 

real-time tracking and dynamic load position sensing. 
HiCASS Target Tracking Sensor Study 

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Table of Contents 

1 Summary ................................................................................................6 

2 Introduction............................................................................................6 

3 Methods, Assumptions, and Procedures ................................................7 

3.1 Evaluations.......................................................................................7 

3.1.1 Precision.....................................................................................7 

3.1.2 Timeliness..................................................................................8 

3.1.3 Impact ........................................................................................8 

3.1.4 Accuracy ....................................................................................8 

3.1.5 Readiness ...................................................................................8 

3.2 Sensors .............................................................................................9 

3.2.1 Ultra Wideband Radio Frequency Identification System..........9 

3.2.2 Three Dimensional Range Camera ..........................................10 

3.2.3 Panning Line Scan LADAR.....................................................12 

3.2.4 Fanning Laser Tracker .............................................................13 

3.2.5 Scanning Laser Tracker ...........................................................13 

4 Results and Discussions.......................................................................13 

4.1 UWB RFID ....................................................................................13 

4.1.1 Accuracy ..................................................................................14 

4.1.2 Precision...................................................................................15 

4.1.3 Timeliness................................................................................15 

4.1.4 Impact ......................................................................................16 

4.1.5 Readiness .................................................................................16 

4.2 3-D Range Camera.........................................................................16 

4.2.1 Accuracy ..................................................................................17 

4.2.2 Precision...................................................................................18 

4.3 Panning Line Scan LADAR...........................................................22 

4.4 Fanning Laser Tracker ...................................................................22 

4.5 Scanning Laser Tracker .................................................................23 

5 Conclusions..........................................................................................24 

6 Recommendations................................................................................25 

6.1 UWB RFID ....................................................................................25 

6.2 3-D Range Camera.........................................................................25 

6.3 Panning Line Scan LADAR...........................................................25 

6.4 Fanning Laser Tracker ...................................................................25 

6.5 Scanning Laser Tracker .................................................................25 

6.6 Vision.............................................Error! Bookmark not defined.

7 References............................................................................................26 

List of Figures 

Figure 1. Sample Mean Position Error and Standard Deviation vs. Tag Height 15 

Figure 2. Position Precision vs. Tag Repetition.........................................15 

Figure 3. Lens Effect on Distance and Precision.......................................17 
HiCASS Target Tracking Sensor Study 

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Figure 4. Lens Effect on Distance and Precision, Near Surface................17 

Figure 5 Reading vs. Distance Correlation................................................18 

Figure 6 Prediction Interval vs. Distance...................................................18 

Figure 7 Prediction Interval vs. Surface Angle..........................................19 

Figure 8. Corner Detection at 1.5 m ..........................................................20 

Figure 9. Corner Detection at less then 0.5m ............................................20 

Figure 10. Corner Detection at 5 m ...........................................................21 

List of Tables 

Table 1. UWB Tag Standard Deviation by Position and Height ...............14 

Table 2. Comparison Summary .................................................................24 
HiCASS Target Tracking Sensor Study 

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1 Summary 

The Expeditionary Logistics Future Naval Capability program intends to generate 

substantial improvements in the skin-to-skin variants of underway Connected 

Replenishment through the High Capacity Alongside Sea base Sustainment program 

(HiCASS). HiCASS requires solutions in many technologies including real-time tracking 

and dynamic load position sensing. The Intelligent Systems Division (ISD) of the 

National Institute of Standards and Technology (NIST) is investigating promising sensors 

for the HiCASS program. This paper reports an investigation on Ultra Wide Band Radio 

Frequency Identification tag. 

2 Introduction

The Expeditionary Logistics Future Naval Capability program (ExLog FNC) identifies 

mature and evolving logistics technologies that, through focused investment, guidance 

and management, can provide enabling capabilities to the modern warfighter. The ExLog 

FNC intends to make a major impact on at-sea transfer of cargo through the High 

Capacity Alongside Sea Base Sustainment (HiCASS) program. HiCASS offers new 

approaches for fuel, cargo, vehicle and personnel transfer in a seaway while underway. It 

is intended to address both transfer between two large vessels and transfer from a large 

vessel to a small vessel. 

The HiCASS program will develop innovative and integrated technology solutions built 

on existing naval systems. The typical naval Connected Replenishment (CONREP) 

method is the Standard Tensioned Replenishment Alongside Method (STREAM). The 

HiCASS program intends to generate substantial improvements to CONREP through 

skin-to-skin cargo transfer. HiCASS requires solutions in many technologies including: 

• Real-time tracking/sensing of own ship/platform motions and those of the other 

ship/platform involved in the at-sea material transfer

• Motion compensating transfer systems capable of the precision required 

• Distance Sensing

• Load Position/ Dynamics Sensing[1]

To fulfill the requirements in these and related technologies, HiCASS must develop and 

utilize appropriate sensory systems. The Intelligent Systems Division (ISD) of the 

National Institute of Standards and Technology (NIST) is investigating promising sensors 

for the HiCASS program. Ultra Wideband Radio Frequency Identification Tracking 

(UWB or UWB RFID) uses small transmitters mounted on the ISO container and an 

array of receivers mounted on the crane to determine the container position via 

triangulated differential arrival times. A Time-Of-Flight Range Camera (a.k.a. flash 

LADAR) uses the time-of-flight of reflected light to measure the distance to relatively 

close surfaces in a video field of view. A panning line-scan LADAR assembles a series 

of two dimension lines into a more accurate three dimension image. A LASER Tracker 

uses transmitters mounted on the crane and a receiver mounted on the container (or 

container ship) to determine position through angular relationships and the time-of-flight 
HiCASS Target Tracking Sensor Study 

 7 

os a single beam. This paper reports an investigations into these sensors and a 

comparison between them. 

3 Methods, Assumptions, and Procedures 

3.1 Evaluations 

We use five criteria to evaluate the sensor system’s ability to track ISO containers for 

HiCASS. The sensor data must be accurate, precise, and timely. The ideal sensor 

candidate also has minimum impact on operating procedures and is available in a 

hardened commercial package. Accuracy is the conformity of a measurement to the 

actual value. Precision is the degree of mutual agreement among a series of individual 

measurements. Timeliness is the time between periodic data sets. Impact is a subjective 

observation of additional burdens placed on the crew. A hardened commercial package is 

one designed for exterior use, preferably for harsh and maritime environments. We rank 

the criteria in order of significance as; precision, timeliness, impact, accuracy, and 

readiness. 

3.1.1 Precision 

This report emphasizes precision in its evaluations. While accuracy is a similar measure, 

accuracy can be corrected through calibration. Precision must be inherent in the sensor. 

NIST specifies the proper expression of uncertainty in TN 1297 [ref]. In this application, 

we concern ourselves with the precision of the sensor’s next reading rather then the 

measurement of the last reading. Therefore, we express the sensor’s precision with the 

magnitude of the prdiction interval. 

The prediction interval is the sum of the mean and the product of the standard deviation 

of sample readings, the t-distribution for the desired confidence, and a function of the 

number of readings of the subsequent sample[9]. 

PI = μ ±σ ntn−1, A 1+1 m (1) 

We use the size of the interval and a 0.95% confidence to compare precision. 

P = σ ntn−1, 0.95 1 +1 m (2) 

For example, when the standard deviation is taken from 25 readings, n=25. Our interest is 

in the accuracy of the next reading, so m=1. With a desired certainty of 0.95 the 

prediction interval is 2.9 times the standard deviation. 

The ultimate goal for the HiCASS controller is to mate an ISO corner post with an ISO 

corner fitting. The post to fitting tolerance is ±3 cm. To ease the tolerance requirement, 

port crane spreader bars use fingers that slide along the ISO container and guide the post 

into the corner fitting. With guide fingers, the overall tolerance is up to ±30 cm. The 

combination of crane errors and the sensor errors must be less then this tolerance. We 

allocate one quarter of the tolerance for tracking sensor errors. Therefore the sensor must 

report position within 0.75 cm for mating without guide fingers and 7.5 cm for mating 
HiCASS Target Tracking Sensor Study 

 8 

with guide fingers. These values are subject to change based on developments of the 

control system. 

3.1.2 Timeliness 

Timeliness is the frequency of periodic data sets. Tracking sensors provide real-time 

positions in a dynamic environment. The position data must be sufficient to trace the 

target’s motion and generate reasonable predictions of its future position. We use a goal 

of 20 Hz in our evaluation for HiCASS. Subsequent developments of the HiCASS 

control system may dictate a higher or lower frequency. 

We base our evaluation of the sensor’s data frequency on the manufacturer’s claims. All 

sensors require additional computations to produce usable positions for HiCASS. We do 

not include these subsequent evaluations in the analysis. When the manufacturer claims a 

data frequency less then 20 Hz, this report explores methods to enhance the output 

frequency. 

3.1.3 Impact 

Impact is a subjective evaluation of burdens imposed on the tracking procedure by the 

sensor. Ideally, sensor operation requires no specific activity or procedure. Minor and, in 

some cases, major impacts may be acceptable for HiCASS. 

A minor impact limits HiCASS motions or requires extra motions. We consider spreader 

bar motion restrictions, such as to avoid obstructing the sensor, to be a minor impact. 

Likewise, the impact is minor when a sensor requires special manipulation by spreader 

bar to track the target. 

Significant impact requires the cargo ship’s crew to perform some duty. A major impact 

is a requirement for the cargo ship’s crew to attach targets to the ISO container. Since the 

ship’s crew must unlash containers and activate twist locks, a quick adjustment to a 

device on the ISO container is a minor impact. 

3.1.4 Accuracy 

Accuracy is the conformity a measurement to the actual value. Since proper calibration 

provides suitable accuracy, ease of calibration (particularly linearity) is a suitable 

measure for accuracy. We report detrimental impacts from minor environment changes as 

a loss of accuracy. 

Any sensor that is repeatable, may be made accurate through calibration. Therefore we 

rank accuracy to be less important then precision, timeliness, and impact. 

3.1.5 Readiness 

Readiness is a subjective evaluation of the commercial status of the sensor. We feel 

HiCASS should not be dependent on significant sensor developments. The sensor’s 

package indicates the maturity of the sensor system and reflects the sensor’s reliability. A 
HiCASS Target Tracking Sensor Study 

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hardened commercial package is one designed for exterior use, preferably for harsh and 

maritime environments. Commercial packaging is not a requirement. The HiCASS 

developers may package any sensor to operate in a maritime environment. Therefore, 

readiness is the lowest priority criteria. 

3.2 Sensors 

This study reviewed five sensor types. Verifying experiments were conducted on some 

sensors, while other sensor evaluations rely on previous NIST investigations. Where 

appropriate, NIST investigations are supplemented with the manufacturer’s claims. 

3.2.1 Ultra Wideband Radio Frequency Identification System 

An Ultra Wideband Radio Frequency Identification (UWB) system tracks embedded 

transmitters through their broadcast of short RF waveforms. Software solves for a signal 

source via the mathematical intersection of multiple hyperbolae as defined by the time 

difference of arrival (TDOA) of the signal at multiple receivers. The PAL650 Precision 

Asset Locator from Multispectral Solutions, Inc. represents the UWB tracking systems 

for this report. The UWB system consists of four (or more) passive Ultra Wide Band 

receivers, a collection of transmitters (a.k.a. tags) and a processing hub. 

 The UWB tags consist of a short pulse transmitter with a peak output power of 

approximately 0.25 Watts. Each tag periodically transmits a 72 pulse burst at 1 Mb/s. 

The burst includes data that uniquely identifies the tag, synchronization fields, and 

control bits. The UWB system’s bandwidth is 1.25 GHz. The bandwidth allows the signal 

to penetrate and circumvent obstacles. While the tags are asynchronous, the bursts are 

very short and collisions are infrequent. 

The difference between the arrival time of two receivers defines a hyperbola of possible 

tag locations. A nonlinear optimization algorithm determines the 3-D tag coordinates 

from three or more hyperbolae. The receivers measure first time-of-arrival via a 100 

MHz clock with a 10-tap digital delay. Since the equations use differential time of arrival 

and there are commonly 4 receivers generating 3 time differentials, the time quantization 

is approximately 300 pS. 

UWB is a relatively low precision device. Improvements in timing, synchronization, 

search algorithms, and averaging may improve accuracy and precision. Timing is flexible 

based on the customer’s requirements. Synchronization and algorithms are ongoing 

efforts of the manufacturer. NIST’s effort evaluates accuracy and precision 

improvements through averaging. We estimate the effects of averaging through a Monte 

Carlo simulation. From the standard deviation of position in each of the major axes and 

random variables, software generates several thousand positions that are averaged and 

filtered to determine their relative impact on the output position. 

The UWB system will have minor or no impact on the cargo ship. The Naval Facilities 

Engineering Service Center (Port Hueneme, CA) is evaluating UWB as a candidate in the 

ONR Naval Total Asset Visibility (NTAV) program[6]. If the Navy selects UWB 
HiCASS Target Tracking Sensor Study 

 10 

tracking, all cargo will arrive at HiCASS with tags. However, HiCASS requirements are 

far greater then NTAV’s and modifications will be required. 

We make the precision and accuracy evaluations based on sample data. NIST uses UWB 

to track small robots in the Urban Search and Rescue test courses[7]. Researchers collect 

information on the tag’s accuracy and precision through a series of static tests. We base 

the accuracy evaluation on the system’s response to changes in the operating 

environment and the precision evaluation on a Monte Carlo simulation. 

Accuracy, readiness, and frequency are evaluated through published accounts and 

antidotal experience of the PAL650 system. Accuracy is a function of the impact of noise 

and obstructions. Readiness reflects the level of the system hardening. Frequency is a 

function of the timing characteristics of the system. All five criteria are compared to 

other sensor options. 

3.2.2 Three Dimensional Range Camera 

The 3D range camera is a solid-state optical device for real-time three dimensional 

imaging. The range camera measures the phase relationship of reflected RF-modulated 

light at each pixel on a video array. The phase relationship correlates to the light’s time 

of flight and measures the distance to a surface. The Swiss Ranger TM 2 from CSEM SA 

[3] represents the 3D range camera systems for this report. The device generates intensity 

and distance values for each pixel of a 124x160 array. The 3D range camera is also 

known as a time-of-flight range camera and a flash ladar. We use these terms 

interchangeably. 

Documented precision studies were not available for the Swiss Ranger TM 2. Therefore, 

experimenters took extensive measurements with the range camera. We measured 

precision in regards to distance, angle, and as derived from the data image. These 

measurements quantified the camera’s precision and provided understanding to the 

operation requirements. 

Experimenters determine the precision as a function of the surface distance from data 

taken at several distances. Experimenters maintain the surface angle at each distance. A 

graphic representation shows the relationship between the prediction interval and the 

distance. 

Experimenters determine the precision as a function of the surface angle by computing 

the prediction interval at several angles. Experimenters adjust the perpendicular distance 

to the surface such that the distance to the reflected point remains constant. A graphic 

representation shows the relationship between the prediction interval and the angle. 

3.2.2.1 Precision of Derived Position 

A range camera has sub-centimeter resolution but far less then centimeter precision. As 

will be shown in the Results section below, the prediction interval for each pixel exceeds 

the HiCASS tolerance requirements. However, there are over 22,000 pixels in each 
HiCASS Target Tracking Sensor Study 

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image. Detection algorithms filter the image to remove egregious noise, smooth data, 

extract prominent features and identify location. 

A range camera is a relatively short-range device. Current RF modulation technology 

limits surface acquisition to 7.5 m. Beyond this range, the detection suffers from 

insufficient returns and aliasing (e.g., an 8.5 m return is indistinguishable from a 1 m 

return). The range camera’s optic Field Of View requires a range greater then 7.5 m to 

view a 6.1 m by 2.4 m (20 ft by 8 ft) surface. Therefore, the observation of an entire ISO 

container by the flash ladar is impossible. Instead, the range camera identifies position 

from the detection of prominent features on the ISO container. 

The most prominent ISO container features are the upper corner fittings. The typical 

corner is at the confluence of one vertical and two horizontal edges. The location of three 

corners will uniquely identify the position and orientation of the container. Since the 

range camera cannot view the entire ISO container, several range cameras need to 

identify separate features on the container. The experiments use a single range camera 

and the target is a single corner of an ISO container. 

3.2.2.1.1 Data Collection Procedure 

The experimenters compensated for some operation limitations of the test unit. The 

experimenters did not adjust collection parameters, but did adjust the lens and collected 

data in supportive environments. All collection positions were from the octant that is 

above, to the side, and in front of the ISO container to limit the subsequent data 

processing. 

The Swiss Ranger TM 2 has integration and threshold parameters to compensate for 

ambient light and surface reflectivity. Data is not currently available that identifies proper 

setting for given conditions and compilation of that data is beyond the scope of this 

effort. Therefore, this report reflects the values generated by the default settings. 

The sample range camera performed poorly in daylight. Therefore, measurements of the 

ISO containers were collected after dark. The calibration and precision data 

measurements were taken indoors. 

The range camera uses a manually adjusted lens. The lens position has a significant 

impact on the quality of the camera’s intensity image and a smaller effect on the distance 

measurements. Lens position effects the focal length and the individual pixel vectors. For 

these experiments, operators adjust the lens for each data reading but use a single lens 

position for calibration readings. 

The experimenter collects data from numerous distances from an ISO corner. All 

collection positions are from the octant that is above, to the side, and in front of the 

container. The experimenter moves the range camera , adjusts the lens to sharpen the 

intensity image, and collects images. Subsequent processing determines the corner 

position. The octant selection limits the number and complexity of required detection 

algorithms. A range camera implementation in HiCASS must function in all seven of the 

empty octants and will require several more detection algorithms. 
HiCASS Target Tracking Sensor Study 

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3.2.2.1.2 Detection Algorithms 

The experimenters developed two algorithms to detect the ISO corner from a range 

image. The first interpretation software identifies the intersection of the container’s two 

top edges. The second interpretation searches the image for the closest point, or nose. 

Software uses the second method when the first cannot find sufficient edges. HiCASS 

will require several algorithms and selection criteria in order to follow the ISO container 

in 3D space. 

The primary interpretation algorithm identifies the ISO container’s top edges and 

computes their intersection point. The algorithm inspects each vertical line for a convex 

edge. The slopes of linear reductions of the 5th through 15th pixel above and below each 

pixel determines the intersecting angle. The pixel with the greatest intersecting angle 

marks the convex edge. The algorithm collects a sequence of edges, estimates the corner, 

computes the lines before and after, and computes the intersection point. Although 

detecting the third edge into the corner would improve the results, the algorithm did not 

use the vertical edge. 

The second interpretation algorithm searches the image for the closet point. This 

algorithm can only detect the corner from limited positions. The algorithm uses 

aggressive noise reduction and heavy filtering to smooth the image and clarify the closest 

point. As with the edge detection algorithm, the sensor must be above, outside, and in 

front of the container for the algorithm to function. The algorithm is useful when the ISO 

container is extremely close or when the container is extremely far away and accuracy 

requirements are relaxed. 

Both algorithms post-process images saved in data files. For HiCASS, the interpretation 

algorithm will execute in real-time. 

3.2.3 Panning Line Scan LADAR 

Line Scan LADARs are popular in motion control systems. A single line scan generates a 

two dimensional map of the world in front of the sensor but cannot track a target in three 

dimensional space. Several tracking options derive from the line scan ladar. One option 

mounts the line scan ladar on a rotating axis. The axis steps across the scene as the ladar 

scans each line. This results in a three dimensional image with accuracy and precision of 

a line scan ladar. The LMS211 from Sick, Inc. is the representative line scan ladar for 

this report [3]. 

NIST is familiar with two panning line scan ladars, both based on the Sick LMS. The 

first mounts the Sick LMS along the axis of a stepper motor. The second reflects the laser 

with a tilting mirror. Both options are laboratory prototypes and both are relatively slow. 

The Sick LMS has an absolute range limit of 80 m (260 ft). However, the system 

accuracy diminishes significantly in the long range mode. We use the short range mode 

(30 m, 98 ft) data for accuracy and precision evaluations. 

The Sick LMS211 takes 101 readings per 13 ms. The readings are every 1° and the scan 

covers 100° in front of the unit. The LMS211 begins a scan at either 50°, 49.75°, 49.5°, 
HiCASS Target Tracking Sensor Study 

 13 

or 49.25°. Thus, the LMS211 can read distances at 1/4° intervals in 53 ms and 1/2° 

intervals in 26 ms. We use the 1° scan for timeliness comparisons. 

3.2.4 Fanning Laser Tracker 

The fanning laser tracker is a system of laser transmitters and active receivers. The 

transmitters send a fan of laser light through the operating environment. The fan’s period 

identifies the transmitter to the receiver. The receiver measures the angles to the 

transmitters and computes the receiver’s relative position from the difference between 

those angles. The fanning laser tracker derives positions for an unlimited number of 

receivers and automatically reacquires position after an interruption. The fanning laser 

tracker for this report is the Constellation 3D-I system from Arc Second, Inc. [4] 

In this report, we use the manufacturer’s data and supplement with other data where 

available. NIST researchers have experience with the Constellation system and we 

include their impressions. Most of the data is from a 2001 aircraft manufacturer’s effort 

to measure the overall accuracy of the Constellation system. 

The Constellation system began tests at sea in November 2004. NSWC-Carderock 

mounted the Constellation system on a T-ACS ship to monitor the motion of a crane 

boom. Test results are not yet available. 

3.2.5 Scanning Laser Tracker 

The scanning laser tracker scans a small area of the environment to track a highly 

reflective target. The target may be passive or active. High accuracy angular servos aim 

the LADAR transmitter at the target. A controller computes the target position from the 

angles and the LADAR distance. An active target derives the target’s orientation from the 

incidence angles. We use the Laser Tracker II with the Smart Trak active target system 

by Automated Precision, Inc. for comparisons in this report[5]. 

We use manufacturer’s data for all comparisons. 

4 Results and Discussions 

4.1 UWB RFID 

The experiment’s UWB system uses four receivers mounted in the corners of a 10 m by 

20 m rectangle, 3 meters above the floor. The lateral spacing approximates a HiCASS 

implementation. The receivers’ height reflects the available facility but is lower and 

flatter then desired. Since all of the receivers were at the same height, the results in the Z 

direction are worse then anticipated for HiCASS. However, since the receivers are closer, 

the X and Y direction results are better then would be anticipated for HiCASS. 

Error! Reference source not found. lists the standard deviation for several hundred 

readings at numerous tag positions in NIST’s USAR arenas. The test covers many 
HiCASS Target Tracking Sensor Study 

 14 

locations within the arena and vertical shifts at those locations. We use the vertical shift 

data to evaluate accuracy and the standard deviation to evaluate precision. 

Table 1. UWB Tag Standard Deviation by Position and Height 

Tag X Y Z 

126 0.081 0.168 0.276 

127 0.089 0.149 0.131 

128 0.069 0.118 0.244 

129 0.074 0.167 0.215 

130 0.085 0.131 0.238 

131 0.067 0.090 0.214 

133 0.091 0.170 0.233 

134 0.124 0.187 0.013 

135 0.087 0.153 0.284 

4.1.1 Accuracy 

Figure 1 displays the mean position error and standard deviation as tags move away from 

the floor. The change in mean error with height shows the impact of environmental 

changes on reported position. Users correct a constant mean error through calibration. 

Since the change in mean error exceeds the HiCASS limit (12 cm vs. 7.5 cm), the UWB 

system does not have sufficient accuracy for HiCASS. 
HiCASS Target Tracking Sensor Study 

 15 

Figure 1. Sample Mean Position Error and Standard Deviation vs. Tag Height 

0

10

20

30

40

50

0 0.5 1 1.5

Tag Height (/m)

Mean Error

Standard Deviation

4.1.2 Precision 

Figure 2 shows the relationship between precision and tag averaging as determined by 

the Monte Carlo simulation. 40 tags achieve the desired precision of 7.5 cm. 40 tags may 

be 40 individual tags or one tag transmitting 40 times per sample. The current tags 

transmit once per second while the tag’s maximum burst rate is 5000 Hz [2]. 

Figure 2. Position Precision vs. Tag Repetition 

4

6

8

10

12

14

10 30 50 70

# Tags Averaged

Prediction Interval (/cm)

4.1.3 Timeliness 

A coordinate system requires a minimum of three points to identify the origin and the 

primary axes. We envision each container will have three tag locations. Two containers 

will be active during tracking. The second provides the ship’s motion when the target 

container is attached to the spreader bar. 
HiCASS Target Tracking Sensor Study 

 16 

The maximum position rate is inverse of the product of the number of tags, the chirps per 

tag, the number of bits per chirp, and the duration of one bit. Therefore, the UWB system 

can generate 57 positions per second (1/(6 tags x 40 chirps/tag x 72 bits/tag x 1μs/bit)). 

The HiCASS requirement of 20 positions per second requires a 35% duty cycle. This 

high duty cycle requires coordination between the transmitters to avoid interference. 

Therefore, the UWB system fulfills the HiCASS timeliness requirement, but may require 

substantial system modifications. 

4.1.4 Impact 

The UWB asset location system is a candidate for ONR’s Naval Total Asset Visibility 

program. If UWB is selected, all DoD ISO containers will have identification tags. 

However the NTAV requires accuracy only within 1.6 m (5 ft) every few seconds [6]. 

HiCASS requires silence by most tags and 800 chirps per second by a few tags. The 

implementation requires the crew to change the tag mode when releasing or engaging the 

corner post twist locks. Therefore there would be minimal impact on the operations of the 

cargo ship’s crew. 

4.1.5 Readiness 

Multi Spectrum Inc. manufactures the UWB system for interior applications. As 

described in previous sections, HiCASS requires significant enhancements. The UWB 

system is not ready for deployment. 

4.2 3-D Range Camera 

The 3-D range camera has adjustable thresholds, saturation limits and a mechanical lens. 

The thresholds and saturation limits correct data for environmental conditions and 

surface reflectivity. The lens focuses the image onto the pixel array. Experimenters did 

not adjust the image thresholds or saturation limits in the range camera’s software. 

However, the camera focus had significant impact on close-in images. Since the 

HiCASS application requires close in observations, experimenters adjusted the camera 

lens to improve focus. 

Figure 3 displays data collected from a stationary range camera 1.5 m from a 

perpendicular surface. The data shows the effect of the lens focus on the distance 

readings and the prediction interval of individual pixels. Clearly the operator desires the 

lens to be in the full CCW position to obtain the tightest prediction interval. 
HiCASS Target Tracking Sensor Study 

 17 

Figure 3. Lens Effect on Distance and Precision 

17000

17100

17200

17300

17400

17500

17600

17700

17800

0 2 4 6 8 10 12

Lens Position (turns cw)

600

800

1000

1200

1400

1600

1800

2000

2200

Prediction Interval

Figure 4 displays the same type of data collected from the same camera at roughly one 

half the distance from the surface. When the lens is fully CCW, the image is unusable. A 

useful image requires several turns of the lens. 

Figure 4. Lens Effect on Distance and Precision, Near Surface 

0

2000

4000

6000

8000

10000

12000

14000

0 2 4 6 8 10 12

Lens Position (turns cw)

0

2000

4000

6000

8000

10000

12000

14000

Prediction Interval

The HiCASS application requires the range camera to operate at various distances 

including, and arguably most importantly, very close. Therefore, the operators adjust the 

lens to provide the clearest image for the ISO identification experiments. Since the lens 

adjustment effects the focal length and, thereby, the pixel unit vectors, subsequent 

evaluation uses the range camera’s distance precision not absolute position accuracy. 

4.2.1 Accuracy 

Users must convert the range camera’s integer distance measures into engineering unit 

values. The experimenters collect data at several positions from a surface and correlate 

the readings with the distance. Since the optical focus impacts the data at close ranges 

Prediction Interval 

Distance Reading 

Prediction Interval 

Distance 
HiCASS Target Tracking Sensor Study 

 18 

and the experimenters are not able to directly measure the focal length, the data positions 

are at medium to long ranges and the focal length is constant throughout the 

measurements. 

The data in Figure 5 has a linear coefficient is 0.000114 m/bit with a –0.365 m offset. 

Subsequent evaluations in this report use these coefficients even with images from 

different focal lengths. The coefficient of determination is 0.998 indicating a highly 

linear relationship. The 3-D range camera has sufficient linearity to meet the HiCASS 

accuracy requirement. 

Figure 5. Reading vs. Distance Correlation 

0

1

2

3

4

5

6

10000 20000 30000 40000 50000

Reading

4.2.2 Precision 

Figure 6 shows the prediction interval as a function of distance. While there appears to be 

a slight positive correlation, the coefficient of determination is 0.06 and the relationship 

is not significant. Figure 6 also shows that while the prediction interval of individual 

pixels is not a function of the target distance, it is also obviously too large for the 

application to utilize single pixel ranges. The individual pixels have a prediction interval 

of 15 cm while the HiCASS has a 7.5 cm maximum tolerance. 

Figure 6. Prediction Interval vs. Distance 

0

5

10

15

20

25

0123456

Distance (/m)
HiCASS Target Tracking Sensor Study 

 19 

Figure 7 shows the relationship between the prediction interval and the surface angle. 

The distance between the range camera and the image center is 2 m (79 in) for each data 

set. The results clearly show the prediction interval increases as the surface angle 

increases. 

Figure 7. Prediction Interval vs. Surface Angle 

0

5

10

15

20

25

30

0 20 40 60 80

Incidence Angle (/deg)

 

The prediction interval test results indicate the individual pixels of the range camera do 

not have the required precision for HiCASS. However, the range camera’s image 

contains over 22,000 pixels. The range camera can achieve the required precision through 

filtering and evaluating the entire image. 

4.2.2.1 Target Detection 

The target to be tracked is the corner fitting of the ISO container. For these evaluations, 

we view the target from the opposite octant (above, to the side, and above the container). 

Figure 8 through Figure 10 show examples of the intensity and distance data from the 

range camera at different distances. Each figure shows the intensity data on the left and 

the distance data on the right. The images display significant noise in the distance 

measures particularly around the ground clutter to the right of the ISO container. The 

detection algorithm marks the convex edges with small blue squares and the target corner 

with a larger white square. 

Figure 8 shows a typical image from approximately 1.5 m. The intensity image is faint, 

but recognizable. The detected points on the two horizontal edges on the distance image 

are highlighted. The ground clutter noise in front and to the right of the container is 

prominent. The algorithm can easily evaluate and discard clutter noise. 
HiCASS Target Tracking Sensor Study 

 20 

Figure 8. Corner Detection at 1.5 m 

Figure 9 shows a typical image from less then one half meter. The container’s corner 

fitting is very clear in both the intensity and distance images. The intensity image is very 

bright with some areas near the center washed out. The range camera cannot derive 

distances from the washed out areas as shown by the equivalent blacked out areas in the 

distance image. The detection algorithm found the container corner through the closest 

point algorithm (note lack of light blue squares on distance image). Figure 9 represents 

the current practical detection limit of the range camera. However, proper application of 

saturation limits may extend the range even closer. 

Figure 9. Corner Detection at less then 0.5m 

Figure 10 shows a typical image from over five meters. This range approaches the 

camera’s limit and the intensity response is negligible. However the distance image 

Intensity Image Distance Image 

Corner

Convex Edge

Intensity Image Distance Image 
HiCASS Target Tracking Sensor Study 

 21 

shows a vaguely recognizable form. Large amounts of ground clutter noise is evident. 

Similarly the reflections from the container itself fade as the distance and incidence angle 

increase. However, due to the large amount of data in a range camera image, there is 

sufficient data for the algorithm to detect the horizontal edges and the container corner. 

Figure 10. Corner Detection at 5 m 

The intended target is the corner fitting of an ISO container as viewed from the opposite 

octant. We evaluate the precision of the computed position through the standard 

deviation of readings from 49 sets of data taken from numerous offsets. The 

experimenters compute the standard deviation through the deviation score of the 

readings. The standard deviation is 1.9 cm and the prediction interval for target detection 

is 5.4 cm. This precision meets the HiCASS requirements. 

4.2.3 Timeliness, Impact, and Readiness 

The 3-D range camera generates 20 images per second. The range camera uses nonilluminated images to identify ambient noise. Users may increase the frame rate by taking 

fewer non-illuminated images. However, images at higher frame rates will have more 

noise in dynamic environments. The default rate of 20 images per second meets the 

HiCASS requirement. 

The 3-D range camera has minimal impact on shipboard procedures but is very restrictive 

for HiCASS with the current capabilities. The daylight restriction makes the current 3-D 

range camera unacceptable for HiCASS. We anticipate optical and focal array 

improvements will correct this problem. 

The SwissRanger 2 is a pre-production prototype. The manufacturer uses forced 

convection to cool the electronics. The package is unsealed and suitable only for interior 

office-type environments. The 3-D camera requires significant re-packaging to meet 

HiCASS requirements. 

Intensity Image Distance Image 
HiCASS Target Tracking Sensor Study 

 22 

4.3 Panning Line Scan LADAR 

The linearity of the scanning ladar response, for a given target in a given environment, is 

excellent. However, LADAR accuracy is also a function of environmental conditions. 

Surface reflectivity, temperature, and humidity are three factors that significantly effect 

the range data. According to the manufacturer, distance values may vary by up to 6 cm. 

However, ISO containers have less variable surface reflectivity then the world in general 

and local calibration may compensate for atmospheric effects. Therefore, the accuracy of 

the panning line scan ladar is acceptable for HiCASS. 

The spreader bar mounted sensor must observe beyond the ISO container in order to 

track the vessel after the container is acquired or when delivering a container. The Sick 

LMS reads distances every degree. At 3 m the Sick LMS measures lateral position within 

0.013 times the distance measurement error. The Sick LMS distance readings have a 

standard deviation of 10 mm for 100 samples. This measurement produces a distance 

prediction interval of 2.8 cm and a position prediction interval (vector sum of distance 

and displacement) of 2.9 cm. This precision is acceptable for the HiCASS application. 

The motor mounted ladar reads an image in 5 seconds. The tilting mirror alternative takes 

3.66 s per image in stepping mode and 1.46 s per image in continuous mode. The 

continuous mode image tends to have less lateral accuracy due to coordination 

difficulties between the rotating mirror in the Sick LMS and the tilting mirror. All of 

these times are for low resolution images (1°x1°). A high resolution image (1/4° x 1/4°) 

takes 18.4 seconds. Therefore, the timeliness of the panning line scan ladar is 

unacceptable for the HiCASS application. 

Because the line scan ladar is operated in short range mode, the panning line scan ladar 

would be mounted on the spreader bar. The device would image the target ISO container 

during acquisition tracking and an adjacent container during departure tracking. The 

panning line scan ladar would have no significant impact on the operations of the 

HiCASS manipulator or the cargo ship’s crew. 

The Sick LMS and panning actuators are both COTS products and both are available in 

hardened packages suitable for maritime environments. The HiCASS controller requires 

software to interpret the images and to coordinate the sensor’s action. However, every 

sensor requires such software. Therefore the Panning Line Scan LADAR hardware is 

ready for HiCASS. 

4.4 Fanning Laser Tracker 

Arc Second reports exceptional accuracy and precision for the Constellation 3D-I system. 

The system is fast and, once calibrated, convenient. The system design is suitable for 

external applications and is currently undergoing sea trials. 

Arc Second measures the standard deviation to be 79 μm (0.02 in) from 2 seconds of 

averaged data. Since the Constellation system outputs data at 40 Hz, the 2 seconds 

represents 80 samples and the system would average two readings in the HiCASS 

application. The size of the prediction interval is; 
HiCASS Target Tracking Sensor Study 

 23 

P = 79μm × t(79,0.95)× 1.5 =1.2cm(0.05in)

Arc Second collected the data in an airplane manufacturing facility [4]. The facility was 

a large, temperature controlled room with laser station mounts on the walls and ceiling. 

HiCASS would have neither environmental controls nor as convenient mounting 

locations. However, the Constellation 3D-I system would meet HiCASS requirements 

even if the impact of a harsher environment increased the prediction interval by 600%. 

Fanning laser tracker receivers are available in fixed position and wireless 

configurations. The HiCASS application requires wireless receivers to be configured into 

targets so the position and orientation of the ISO container may be derived. The ship’s 

crew attaches one target to the desired ISO container and another on a nearby container. 

The HiCASS controller tracks the second target after capturing the desired ISO container. 

Between loads the crew would move the targets for the next load. The target on the 

captured container would have to be returned to the cargo ship for reuse. These activities 

are a major impact on the cargo ship’s crew. 

The fanning laser tracker is ready for HiCASS. The Constellation 3D-I system is 

currently undergoing sea trials. Results of these trial will be available within a couple 

months. 

4.5 Scanning Laser Tracker 

The Tracker II exceeds the HiCASS requirements for accuracy and precision. Automated 

Precision manufactures the sensor for industrial environments. However the sensor will 

have major impact on the crew operations and the timeliness may not be sufficient. 

The tracker transmitter may be mounted on the micro-manipulator or on the crane base. 

When mounted on the crane, the micro-manipulator or a crew member may pass between 

the transmitter and receiver, cause an interruption, and lose tracking. The scanning laser 

tracker has fewer problems when mounted on the micro-manipulator. 

We envision the tracker transmitter to be mounted on the micro-manipulator and the 

receiver mounted on the ISO container beneath the target container. The sensor tracks the 

same target upon approach and departure. The sensor follows the same target upon 

approach and departure. The Tracker II claims an dynamic absolute position 3-D 

accuracy of 10 ppm (2 sigma). At 3 m (10 ft), the sensor’s standard deviation is 1.5 cm 

(.06 in) which yields a prediction interval of 0.4 cm. The manufacturer claims an 

orientation resolution of 3 arc-seconds. If uncertainty is 10 times the resolution, the 

additional error for the upper corner fitting is 0.38 mm (0.015 in). This value is sufficient 

to track the ISO container for mating without guide fingers. 

The Smart Trak seriously impacts the ship operations. Because the Smart Trak system 

uses an active receiver, the ship’s crew must transfer receivers between loads. However, 

only the sensor requires only one target for both position and orientation and the target 

weighs about 1.3 kg (3 lbs). The crew can handle the target. 
HiCASS Target Tracking Sensor Study 

 24 

The manufacturer claims several thousand readings per second, which exceeds the 

HiCASS timeliness requirement. However, any interference between the transmitter and 

receiver breaks the link. The tracker requires several seconds to reacquire the receiver 

once the link is lost. 

5 Conclusions 

None of the evaluated sensor systems fulfill all of the HiCASS requirements. Error! 

Reference source not found. shows a comparison between the five alternatives. The 

table displays four levels of compliance with the HiCASS goals. “/” indicates the sensor 

fell significantly below the goal and sufficient improvements are unlikely. The symbol 

“.” indicates the sensor did not meet the requirement but improvements are possible. 

“☺” indicates the sensor fulfills the requirements in that category. “☺☺” indicates the 

sensor exceeds the requirement. The final row summarizes the desired HiCASS criteria. 

Table 2. Comparison Summary 

Sensor Precision Frequency Impact Accuracy Ready 

UWB RFID . . ☺ / .

TOF Range Camera ☺ ☺ . ☺ .

Panning Line Scan ☺ / ☺ ☺ ☺

Fanning Tracker ☺☺ ☺☺ / ☺☺ ☺

Scanning Tracker ☺☺ . / ☺☺ ☺

☺ is < 7.5 cm 20 Hz Minor r2

 > 0.99 Commercial 

The UWB alternative does not have sufficient accuracy, precision, frequency, or 

readiness. The precision and frequency may be improved through modifications to the 

UWB system. Due to the environmental effects, sufficient improvements to the accuracy 

are unlikely. The alternative is attractive due to a low impact on the cargo ship’s crew 

and the potential to operate during periods of low visibility. 

The precision and timeliness of the 3-D range camera meet the HiCASS requirements. 

The range camera alternative adds no burdens to the cargo ship’s crew. The lens system, 

and the need to adjust the lens, diminishes the system accuracy. The range cameras are 

prototypes, are not hardened, and have several inadequacies. The most significant 

problem is the inability to operate in daylight. The manufacturer identifies several 

enhancements that may correct the inadequacies. 

The panning line scan ladar fulfills all of the HiCASS requirements except timeliness. 

The panning line scan requires 20 seconds to capture a high resolution image and 5 
HiCASS Target Tracking Sensor Study 

 25 

seconds for a low resolution image. We include a possible modification in the 

Recommendations section below. 

Laser Trackers have excellent accuracy and precision. We consider two laser trackers. 

Both of the laser trackers have sufficient timeliness and both are hardened commercial 

systems. However both use active targets which must be attached to the containers by the 

cargo ship’s crew. The scanning laser tracker suffers from a 3 second re-acquisition time 

if the transmitter-receiver link is broken. 

6 Recommendations 

Our results justify further investigations into three of the sensor alternatives. 

Consideration of the other two may be discontinued. The HiCASS prime contractor may 

also investigate additional sensors. 

6.1 UWB RFID 

The number of enhancements required to make the UWB usable by HiCASS are 

substantial. The UWB tracking system should be pursued for HiCASS only if the tag 

system has been selected by the NTAV program. 

6.2 3-D Range Camera 

3-D Range Cameras are relatively new devices. Although not ready for HiCASS in their 

current state, the manufacturer acknowledges several improvements which may add 

sufficient capabilities. These include IR lens designs with coatings to reduce glare and 

the use of LASER diodes for illumination. The HiCASS program should encourage the 

manufacturer to make these improvements. If the improvements correct the sensor’s 

deficiency, the 3-D range camera would be an excellent target tracking sensor for 

HiCASS. 

6.3 Panning Line Scan LADAR 

The Panning Line Scan LADAR meets all of the HiCASS requirements except 

timeliness. Timeliness improvements are not likely. 

6.4 Fanning Laser Tracker 

The Fanning Laser Tracker fulfills most of the HiCASS requirements. The crew impact 

cannot be reduced but may be tolerable. We recommend further investigation. 

6.5 Scanning Laser Tracker 

The Scanning Laser Tracker fulfills most of the HiCASS requirements. The crew impact 

cannot be reduced but may be tolerable. We recommend further investigation. 
HiCASS Target Tracking Sensor Study 

 26 

6.6 Vision 

We did not consider vision based sensor systems. Vision based trackers work well in 

restricted environments. Since ladars have the required accuracy and vision system can 

track objects, a coordinated vision-ladar system may be able to fulfill the HiCASS 

requirements. 

7 References 

[1] ONR BAA Number 04-006. 

[2] “Precision Asset Locator (PAL650) User’s Guide”, Rev 1.4, Multispectral Solutions, 

Germantown, MD, Oct 2003. 

[3] “User manual: SwissRangerTM 2”, Centre Suisse d’Electronique et de Microtechnique 

SA, Zurich, Switzerland, Dec 2003. 

[4] “Indoor GPS Technology For Metrology”, Arc Second White paper #071502, Arc 

Second, Inc., Dulles, VA, 2002. 

[5] “Scanning Laser Tracker” 

[6] Fontana, Robert J. and Gunderson Steven J., “Ultra-Wideband Precision Asset 

Location System”, 2002 IEEE Conference on Ultra Wideband Systems and 

Technologies, Baltimore, MD., May 2002. 

[7] USAR reference 

[8] Fontana, Robert J. et al, “Commercialization of an Ultra-Wideband Precision Asset 

Location System”, 2002 IEEE Conference on Ultra Wideband Systems and 

Technologies, Reston, VA, Nov 2003. 

[9] Vining, G. Geoffrey, Statistical Methods for Engineers, Brooks/Cole Publishing 

Company, Pacific Grove, CA 1998, p176. 

[10] Dong Hun Shin, et al, Proceedings. 2003 IEEE/RSJ International Conference on 

Intelligent Robots and Systems, 2003. (IROS 2003)., Oct 2003.