Method, system, and computer program product for automatic multi-object localization and/or vital sign monitoring
A method for automatic multi-object localization and/or vital sign monitoring is provided. The method comprises the steps of receiving a radar signal in order to form a corresponding observation matrix, reducing noise by applying singular value decomposition to the observation matrix, processing the result of the singular value decomposition by an independent component analysis in order to estimate the corresponding sources, and estimating propagation channels of the estimated sources by minimizing the corresponding residual error based on the observation matrix and the estimated sources.
1. A method for automatic multi-object localization and/or vital sign monitoring, the method comprising:
transmitting a radar signal;
receiving a corresponding transmitted radar signal in order to form a corresponding observation matrix ( X );
reducing noise by applying singular value decomposition to the observation matrix ( X );
processing the result of the singular value decomposition by an independent component analysis in order to estimate corresponding sources (Ŝ), wherein each source is an observed source of vital sign information;
estimating propagation channels (H) of the estimated sources (Ŝ) by minimizing corresponding residual error (∥ X −HŜ∥ 2 2 ) using the observation matrix ( X ) and the estimated sources (Ŝ), wherein each propagation channel is a representation of how a signal is transmitted from the corresponding source to the receiver; and
locating the respective objects using the estimated sources (Ŝ) and estimated propagation channels (H).
2. The method according to claim 1 ,
wherein before the independent component analysis, the method further comprises estimating a number of respective targets, by calculating the signal-to-noise ratio of respective uncorrelated sources in the result of the singular value decomposition.
3. The method according to claim 1 ,
wherein the method further comprises removing respective order ambiguity using the estimated propagation channels (Ĥ).
4. The method according to claim 1 ,
further comprising performing a phase demodulation with respect to the estimated sources (Ŝ).
5. The method according to claim 4 ,
further comprising extracting the respective vital sign information or signal (ŷ(t)) from the time domain signals (ŝ(t)) of the estimated sources (Ŝ) after the phase demodulation.
6. The method according to claim 5 ,
wherein the extracting is performed using the following equation:
y
ˆ
(
t
)
=
s
ˆ
(
t
)
λ
0
4
π
,
wherein λ 0 denotes the corresponding wavelength at the first frequency of a respective chirp signal, and
wherein π denotes the constant Pi.
7. The method according to claim 5 ,
further comprising obtaining corresponding respiration and heartbeat signals by performing a filtering operation with respect to the respective vital sign information or signal (ŷ(t)).
8. The method according to the claim 7 ,
further comprising estimating corresponding heart rates by performing a frequency transform with respect to the respective respiration and heartbeat signals.
9. The method according to claim 8 ,
wherein the frequency transform comprises or is a fast Fourier transform.
10. The method according to claim 5 ,
further comprising obtaining the corresponding respiration and heartbeat signals by performing a wavelet decomposition with respect to the respective vital sign information (ŷ(t)).
11. The method according to claim 5 ,
further comprising obtaining the corresponding respiration and heartbeat signals by performing a Hilbert transform and/or further convex optimization steps with respect to the respective vital sign information or signal (ŷ(t)).
12. The method according to claim 1 ,
wherein the radar signal comprises a chirp signal.
13. The method according to claim 1 ,
wherein the radar signal originates from a frequency-modulated continuous wave radar.
14. A system for automatic multi-object localization and/or vital sign monitoring, the system comprising:
a transmitter; and
a receiver; and
a processor,
wherein the transmitter is configured to transmit a radar signal, the receiver is configured to receive a corresponding transmitted radar signal in order to form a corresponding observation matrix ( X ), and
wherein the processor is configured to reduce noise by applying singular value decomposition to the observation matrix ( X ), to process the result of the singular value decomposition by an independent component analysis in order to estimate corresponding sources (Ŝ), wherein each source is an observed source of vital sign information, to estimate propagation channels (H) of the estimated sources (Ŝ) by minimizing corresponding residual error (∥ X −HŜ∥ 2 2 ) using the observation matrix ( X ) and the estimated sources (Ŝ), wherein each propagation channel is a representation of how a signal is transmitted from the corresponding source to the receiver, and to locate the respective objects using the estimated sources (Ŝ) and estimated propagation channels (H).
15. A non-transitory computer-readable medium storing a computer program, which, when read and executed by a computer causes the computer to perform a method of automatic multi-object localization and/or vital sign monitoring, the method comprising:
transmitting a radar signal;
receiving a corresponding radar signal in order to form a corresponding observation matrix ( X );
reducing noise by applying singular value decomposition to the observation matrix ( X );
processing the result of the singular value decomposition by an independent component analysis in order to estimate corresponding sources (Ŝ), wherein each source is an observed source of vital sign information;
estimating propagation channels (H) of the estimated sources (Ŝ) by minimizing corresponding residual error (∥ X −HŜ∥ 2 2 ) using the observation matrix ( X ) and the estimated sources (Ŝ), wherein each propagation channel is a representation of how a signal is transmitted from the corresponding source to the receiver; and
locating the respective objects using the estimated sources (Ŝ) and estimated propagation channels (H).