Multifaceted radiation detection and classification system
A system identifying a source of radiation is provided. The system includes a radiation source detector and a radiation source identifier. The radiation source detector receives measurements of radiation; for one or more sources, generates a detection metric indicating whether that source is present in the measurements; and evaluates the detection metrics to detect whether a source is present in the measurements. When the presence of a source in the measurements is detected, the radiation source identifier for one or more sources, generates an identification metric indicating whether that source is present in the measurements; generates a null-hypothesis metric indicating whether no source is present in the measurements; evaluates the one or more identification metrics and the null-hypothesis metric to identify the source, if any, that is present in the measurements.
1 . A method performed by a computing system for generating a metric relating to a measurement of a source of radiation, the method comprising:
causing a radiation source detector to engage in long-term historical local background radiation measurements;
causing the radiation source detector to capture a source signature of the measurement of the source;
accessing, by a radiation source detector, a source signature of the measurement of the source and an estimated background, the estimated background based on the historical local background radiation measurements;
generating a first hypothesis based on the estimated background and an estimated background rate;
generating a second hypothesis based on the estimated background, the estimated background rate, and the source signature;
generating a first likelihood for the first hypothesis given a Poisson distribution;
generating a second likelihood for the second hypothesis given the Poisson distribution;
generating a projection vector based on the first likelihood and the second likelihood;
accessing a measurement of a physical quantity of radiation via a radiation detector; and
generating, by the radiation source detector, the metric based on the measurement, the projection vector, and the estimate background rate.
2 . The method of claim 1 wherein the source signature is a histogram representing an energy range divided into energy bins, each energy bin having a value representing a count of photons emitted by that source over a time interval.
3 . The method of claim 1 wherein a source signature represents a shielding of the source.
4 . The method of claim 1 further comprising generating aggregated measurements of multiple measurements of physical quantities of radiation and for each aggregated measurement, generating a metric based on the aggregated measurement and the projection vector.
5 . The method of claim 1 further comprising when the metric satisfies a source present threshold, indicating that presence of the source has been detected.
6 . The method of claim 1 further comprising when the metric satisfies a source present threshold, indicating that presence of the source has been semi-definitively detected.
7 . One or more computing systems comprising:
one or more computer-readable storage mediums for storing computer-executable instructions, execution of which causes the one or more computing systems to:
cause a radiation source detector to engage in long-term historical local background radiation measurements;
cause the radiation source detector to capture a source signature of a measurement of a source of radiation;
access, by a radiation source detector, the source signature of the measurement of the source of radiation and an estimated background, the estimated background based on historical local background radiation measurements;
generate a first hypothesis based on the estimated background and an estimated background rate;
generate a second hypothesis based on the estimated background, the estimated background rate, and the source signature;
generate a first likelihood for the first hypothesis given a Poisson distribution;
generate a second likelihood for the second hypothesis given the Poisson distribution;
generate a projection vector based on the first likelihood and the second likelihood;
access a measurement of a physical quantity of radiation via a radiation detector; and
generate, by the radiation source detector, a metric based on the measurement, the projection vector, and the estimate background rate; and
one or more processors to execute the computer-executable instructions stored in the one or more computer-readable storage mediums.
8 . The one or more computing systems of claim 7 wherein the source signature is a histogram representing an energy range divided into energy bins, each energy bin having a value representing a count of photons emitted by that source over a time interval.
9 . The one or more computing systems of claim 7 wherein a source signature represents a shielding of the source.
10 . The one or more computing systems of claim 7 wherein the instructions aggregate measurements of different numbers of measurements and for each aggregated measurement, generating a metric based on the aggregated measurement and the projection vector.
11 . The one or more computing systems of claim 7 wherein when the metric satisfies a source present threshold, the instructions indicates that presence of the source has been detected.
12 . The one or more computing systems of claim 7 wherein when the metric satisfies a source present threshold, the instructions indicate that presence of the source has been semi-definitively detected.
13 . A method performed by a computing system for generating a metric for indicating presence of a measurement of a source of radiation in measurements of radiation collected in sequence, the method comprising:
causing a radiation source detector to engage in long-term historical local background radiation measurements;
causing the radiation source detector to capture a source signature of the source of radiation;
constructing hypotheses represented by the following equations:
H
0
=
B
s
B
r
Δ
t
H
1
=
B
s
B
r
Δ
t
+
S
s
k
B
r
Δ
t
where H 0 and H 1 are the hypotheses, B s represents a background shape, S s represents a source signature shape, B r represents a background rate estimate, Δt represents change time period, and each shape is a histogram with a total count of 1, wherein the background rate estimate is based on the historical local background radiation measurements of physical quantities of radiation in the predetermined location;
calculating a likelihood of each measurement given Poisson statistics as represented by the following equation:
P
(
X
❘
H
)
=
∏
i
exp
(
-
h
i
)
h
i
x
i
x
i
!
where h i represents the i-th element of the hypothesis;
generating a ratio of the hypotheses as represent by the following equation:
LRT
(
X
)
=
log
(
1
+
k
B
r
Δ
t
S
s
B
s
)
t
X
-
k
B
r
Δ
t
=
T
t
X
+
M
.
generating the metric by as represented by the following equation:
DM
=
(
T
t
X
+
κ
B
r
Δ
t
)
vB
r
Δ
t
where DM represents the metric and K represents a bias term for any difference in the estimated total count in the background and an expected background total count in the background.
14 . The method of claim 13 wherein the source signature is a histogram representing an energy range divided into energy bins, each energy bin having a value representing a count of photons emitted by that source over a time interval.
15 . The method of claim 13 wherein a source signature represents a shielding of the source.
16 . The method of claim 13 further comprising generating aggregated measurements of multiple measurements of physical quantities of radiation and for each aggregated measurement, generating a metric based on the aggregated measurement, a projection vector, and an expected variance for the aggregated measurement.
17 . A method performed by a computing system for adjusting measurement counts of measurements of a physical quantity of radiation via a radiation detector to account for temporary changes in the measurements, the method comprising:
causing a radiation source detector to engage in long-term historical local background radiation measurements;
causing the radiation source detector to capture a source signature of the measurement of the source;
accessing a plurality of measurements of the physical quantity of radiation;
for each of the measurements, generating a measurement count of that measurement;
generating an upper average measurement count that is an average of the measurement counts higher than a threshold count;
calculating an expected offset for a probabilistic distribution based on the upper average measurement count and the measurement counts higher than the threshold; and
for each measurement, subtracting the expected offset from the measurement count for that measurement.
18 . The method of claim 17 wherein the measurements are of radiation and the temporary changes are a result of changes in background radiation.
19 . The method of claim 18 further comprising detecting when the measurements indicate a source of radiation.
20 . The method of claim 19 wherein the detecting is performed using a gross count detection algorithm.
21 . The method of claim 18 wherein the upper average measurement count is based on a probability distribution.
22 . One or more computing system for adjusting measurement counts of measurements to account for temporary changes in the measurements of a physical quantity of radiation via a radiation detector, the one or more computing system comprising:
one or more computer-readable storage mediums for storing computer-executable instructions, execution of which causes the one or more computing systems to:
causing a radiation source detector to engage in long-term historical local background radiation measurements;
causing the radiation source detector to capture a source signature of the measurement of the source;
for each measurement of a plurality of measurements of a physical quantity of radiation via a radiation detector, generate a measurement count of that measurement;
generate an upper average measurement count that is an average of the measurement counts higher than a threshold count;
calculate an expected offset for a probabilistic distribution based on the upper average measurement count and the measurement counts higher than the threshold; and
for each measurement, subtract the expected offset from the measurement count for that measurement; and
one or more processors to execute the computer-executable instructions stored in the one or more computer-readable storage mediums.
23 . The one or more computing systems of claim 22 wherein the measurements are of radiation and the temporary changes are a result of changes in background radiation.
24 . The one or more computing systems of claim 23 wherein the instructions further detect when the measurements indicate a source of radiation.
25 . The one or more computing systems of claim 24 wherein the detecting is performed using a gross count detection algorithm.
26 . The one or more computing systems of claim 24 wherein the upper average measurement count is based on a probability distribution.