Data processing: measuring – calibrating – or testing – Measurement system – Measured signal processing
Reexamination Certificate
2002-02-01
2004-10-19
Bui, Bryan (Department: 2863)
Data processing: measuring, calibrating, or testing
Measurement system
Measured signal processing
C702S190000, C702S191000, C702S196000
Reexamination Certificate
active
06807517
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
The invention relates to a method for estimating the impulse response of a propagation channel, especially its parameters such as the delay values, the directions of arrival as well as the values of the complex amplitudes associated with these parameters, with an a priori knowledge of the signal.
It is applicable, for example, to the estimation of the parameters of a finite impulse response filter which can be written, though not necessarily so, in specular form, namely a filter that can be written in the form of weighted Diracs.
The invention can be used to estimate propagation channels in the field of radiocommunications but also, generally, it can be applied to any signal filtered by a finite impulse response linear filter.
In a transmission system, especially one using radio waves, a transmitter sends out a signal in a transmission channel to a receiver. The signal that is sent undergoes amplitude and phase fluctuations in the transmission channel. The signal received by the receiver consists of copies of the transmitted signal that are temporally shifted and modified. The fluctuations of the signal and the shifts give rise to a phenomenon known to those skilled in the art as inter-symbol interference. The interference arises especially out of the law of modulation used for transmission and also from the multi-path propagation in the channel.
The received signal generally arises out of a large number of reflections in the channel. The different paths taken by the sent signal thus lead to different delays in the receiver. The impulse response of the channel represents the totality of the fluctuations to which the sent signal is subjected.
The estimation of the propagation channel in a radiocommunications system is useful in several respects, some of which are indicated here below as examples.
The demodulators generally require knowledge of the channels in order to remedy the harmful effects that they have caused,
a second point of interest is that of urban or extra-urban localization, for example the principle of emergency localization using the number “911” in the United States
Finally, the knowledge of the propagation channels can also serve for the use of smart antennas at reception as well as transmission,
2. Description of the Prior Art
There are various techniques known in the prior art for estimating propagation channels and their parameters.
For example the document by R. Rick and L. Milsteil, “Performance acquisition in mobile ds-cdma systems”, IEEE Trans on Communications, Vol: 45 (No: 11):pp: 1466-1476, November 1997, proposes a search for propagation delays by using a bank of non-coherent detectors. The results are proposed for multi-path channels in the presence of Doppler phenomena and inter-cell and intra-cell interference.
The document by R. Rick et L. Milsteil, “Optimal decision strategies for acquisition of spread-spectrum signals in frequency selective fading channels” in IEEE Trans. on Communications, Vol: 46 (No: 5):pp: 686-694, May 1998, discloses an optimal decision rule based on the outputs of the correlators proposed in the document referred to here above. A single-user technique of this kind is limited by interference in the case of multiple-users.
There also exist known ways of using rectangular shaping filters, for example by the method described in one of the following documents:
E. Strom, S. Parkvall, S. Miller, and B. Ottersen, “Propagation delay estimation in asynchronous direct-sequence code-division multiple access systems”, IEEE Trans on Communications, Vol: 44:pp: 8-93, January 1996
S. Parkvall, “Near-Far Resistant DS-CDMA Systems: Parameter estimation and Data Detection”, PhD thesis, Royal Institute of Technology Stockholm, Sweden, 1996.
S. E. Bensley and B. Aazhang, “Maximum likelihood estimation of a single user's delay for code division multiple access communication systems”, Conf. Information Sciences and Systems, 1994.
In the case of shaping filters with a duration greater than a chip time, these different methods are no longer suitable.
Algorithms for the combined estimation of angles of arrival and of the differential delay times, on known and received signals, based on sub-space techniques have been proposed, for example in the document by P. Gounon, “Analyse spatio-temporelle haute résolution à l'aide d'une antenne active”, (High Resolution Space-time Analysis Using an Active Antenna) Traitement du Signal (Signal Processing), Vol. 11 (No. 5), pp. 351-360, 1994.
The document by A. J Van der Veen, M. C. Vanderveen, et A. J. Paulraj, “Joint angle and delay estimation using shift-invariance properties”, IEEE Sig. Proc Letters, Vol.4 (No.5): pp. 142-145, 1997, discloses methods for the estimation of the physical parameters of propagation by means of methods based on sub-spaces.
However, such methods suffer from a deterioration of performance characteristics once the impulse responses of the propagation channels are correlated. This situation occurs especially when the complex amplitudes do not vary with sufficient speed on the covariance matrix of the impulse responses estimated in terms of the least-error squares by means of the signal transmitted,
FIG. 1
shows the different techniques of maximum likelihood.
A maximum likelihood method has been proposed, for example, in one of the following references:
J. Grouffaud, “Identification spatio-temporelle de canaux de propagation à trajets multiples”, (Space-time Identification of Multi-Path Propagation Channels), PhD thesis, École Normale Supérieure de Cachan, June 1997.
M. Wax and A. Leshem, “Joint estimation of delays and directions of arrival of multiple reflections of a known signal.”, IEEE Trans. on Signal Processing, Vol: 45(No: 10):pp: 2477-248, October 1997.
but it does not deal with the MIMO (Multiple Input Multiple Output) context.
The document by P. Graffoulière, “Méthodes actives spatio-temporelles large bande” (Active Wideband Space-Time Methods), published in <<Techniques et performances. Applications En Sonar>> (Techniques and Performance. Sonar Applications), PhD thesis, INPG, March 1997, also discloses a method of estimation based on maximum likelihood but the studies on performance deal only with the case of a single source or of several distinctly separate sources. A similar study is disclosed in the document N. Bertaux, “Contribution à l'utilisation des méthodes du Maximum de Vraisemblance en traitement radar actif” (Contribution to the Use of Maximum Likelihood Methods in Active Radar Processing), PhD thesis, Ecole Normale Supérieure de Cachan, January 2000, for active radar applications in the case of single sources.
SUMMARY OF THE INVENTION
The present invention relates to a method that can be used especially to estimate the parameters of the propagation channel by working on the correlated signals, in selecting a certain number of samples and in searching for the values of the delay parameters and/or directions of arrival, for example, which would enable the most efficient reconstruction of the signal received.
The invention also relates to a method that integrates pulse compression techniques such as pre-processing.
The invention relates to a method for the estimation of one or more parameters of a propagation channel with a priori knowledge of the signal in a system comprising one or more sensors.
The method of the invention comprises the following steps:
correlating one or more signals x(t) received by the sensors with the known signal c(t),
sampling the signals at a sampling period Te and selecting a number of samples per concatenation,
determining at least one parameter of the propagation channel, including &tgr; or &thgr;, which enables the most efficient reconstruction of the signals x(t) via a maximum likelihood method.
According to one embodiment, the characteristics of the system of sensors are known and comprise for example:
a correlation step with a known signal c(t) equal to 1,
the signals received on the antenna being expressed in the form X=S(&thgr;,&tgr;)
Adnet Claude
Chenu-Tournier Marc
Chevalier Pascal
Larzabal Pascal
Bui Bryan
Oblon & Spivak, McClelland, Maier & Neustadt P.C.
Thales
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