US 8,138,974 B2 · Location estimation system, method and program

Abstract

A location estimation method using label propagation. The achieved location estimation method is robust to variations in radio signal strengths and is highly accurate by using the q-norm (0<q<1), especially, for calculating the similarities among radio signal strength vectors. The accuracy in location estimation is further improved by putting more importance on the time-series similarities. Specifically, the time-series similarity is calculated by using time-series values indicating the temporal order of radio signal strengths during the measurement. If the time-series similarity is larger than the similarity between the radio signal strength vectors, the time-series similarity is preferentially used. The exponential attenuation function can also be used for calculating the similarities, instead of the q norm (0<q<1).

Claims27

Dependent claims

A system for estimating a location label of a vector dataset without any location label from a plurality of vector datasets respectively with location labels using a computer, the system comprising:

storage means provided in the computer;
means for storing the vector datasets in the storage means of the computer;
means for calculating the similarity between the vector dataset without any location label and each neighboring vector dataset with a location label, by using any one of a q-norm wherein 0<q<1 and an exponential attenuation function;
and
means for estimating the location label of the vector data without any location label from the calculated similarities,
wherein the similarities are calculated by means of the following expression using the q-norm,
WX(i,j)=exp(−∥X(i)−X(j)∥qq),
where X(i) and X(j) denote i-th and j-th vectors, respectively, and

X

q
=
(
∑
d
=
1
n
⁢

X
d

q
σ
d
)
1
q
where n denotes the number of dimensions of the vector and 0<σd<∞.

28 more elements

A location estimation method for estimating a location from radio signal strength datasets by means of a computer, the method comprising the steps of:

preparing a plurality of radio signal strength vector datasets with location labels and a plurality of radio signal strength vector datasets without location labels, respectively, and then storing the prepared datasets in storage means of the computer;
setting, by means of the computer, an initial value of the plausibility score f(i)(c) wherein i=1. . . N and wherein N denotes the number of all the prepared radio signal strength vector datasets such that each of the radio signal strength vector datasets with location labels and the radio signal strength vector datasets without location labels has a location label c;
calculating, using the computer, the similarity W(i,j) for each combination of i and j wherein i,j=1. . . N, by using any one of a q-norm wherein 0<q<1, of the radio signal strength vector and an exponential attenuation function;
calculating, by means of the computer, f(i)(c) for each of the radio signal strength vector datasets without location labels, by using the following expression
f
(
i
)
⁡
(
c
)
=
∑
j
⁢
W
(
i
,
j
)
⁢
f
(
j
)
⁡
(
c
)
∑
j
⁢
W
(
i
,
j
)
;
⁢
and
iteratively executing the step of calculating f(i)(c) by means of the computer.

41 more elements

A program for estimating a location from radio signal strength datasets by means of a computer, the program causing the computer to execute the steps of:

preparing a plurality of radio signal strength vector datasets respectively with location labels and a plurality of radio signal strength vector datasets without location labels, and then storing the prepared datasets into storage means of the computer;
setting an initial value of the plausibility score f(i)(c) wherein i=1. . . N and wherein N denotes the number of all the prepared radio signal strength vector datasets that each of the radio signal strength vector datasets with location labels and the radio signal strength vector datasets without location labels has a location label c;
calculating the similarity W(i,j) for each combination of i and j wherein i,j=1. . . N, by using any one of a q-norm wherein 0<q<1, of the radio signal strength vector and an exponential attenuation function;
calculating f(i)(c) for each of the radio signal strength vector datasets without location labels, by using the following expression
f
(
i
)
⁡
(
c
)
=
∑
j
⁢
W
(
i
,
j
)
⁢
f
(
j
)
⁡
(
c
)
∑
j
⁢
W
(
i
,
j
)
;
⁢
and
iteratively executing the step of calculating f(i)(c).

41 more elements

A system for estimating a location from radio signal strength datasets by means of a computer, the system comprising:

storage means;
means for preparing a plurality of radio signal strength vector datasets respectively with location labels and a plurality of radio signal strength vector datasets without location labels, and then storing the prepared datasets into the storage means;
means for setting an initial value of the plausibility score f(i)(c) wherein i=1. . . N and wherein N denotes the number of all the prepared radio signal strength vector datasets that each of the radio signal strength vector datasets with location labels and the radio signal strength vector datasets without location labels has a location label c;
means for calculating the similarity W(i,j) for each combination of i and j wherein i,j=1. . . N by using any one of a q-norm wherein 0<q<1 of the radio signal strength vector and an exponential attenuation function;
means for calculating f(i)(c) for each of the radio signal strength vector datasets without location labels, by using the following expression
f
(
i
)
⁡
(
c
)
=
∑
j
⁢
W
(
i
,
j
)
⁢
f
(
j
)
⁡
(
c
)
∑
j
⁢
W
(
i
,
j
)
;
⁢
and
means for iteratively executing the step of calculating f(i)(c).

42 more elements

Dependencies are inferred from the claim text.

Location estimation system, method and program

Life of this patent

Location estimation system, method and program

Life of this patent

Abstract

Claims27