Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-4, 6 and 9-12 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Eschbaumer et al (US 2022/0342039 A1), hereinafter Eschbaumer. (Applicant’s cited prior art).
Regarding claim 1, the system of Eschbaumer (Figure 1, para [0050] and [0051]) would enable a method of operating a radar system in which at least one electromagnetic radar signal is transmitted from at least one transmit antenna element of the radar system comprising the steps of:
receiving at least one electromagnetic echo signal resulting from at least one radar signal reflected from at least one target in a field of view of the radar system by at least one receiving antenna element and converting the at least one received electromagnetic echo signal into received data suitable for signal processing (para [0051]);
determining at least one magnitude information and at least one phase information corresponding to the at least one received electromagnetic echo signal from at least a part of the received data (para [0052]);
determining at least one position information by use of machine learning, the at least one position information characterizing at least a direction of the at least one target relative to a reference system, which is related to the radar system (para [0125]),
wherein the radar system is operated as a multiple-input multiple-output radar comprising multiple transmit antenna elements and multiple receiving antenna elements,
wherein the multiple transmit antenna elements and the multiple receiving antenna elements generate a virtual antenna array with multiple virtual antenna elements for receiving electromagnetic echo signals during a multiple- input multiple-output operation of the radar system (Figure 14, para [0114] to [0117]);
determining for at least a part of the virtual antenna elements each a magnitude information and a phase information from the at least one part of the received data by performing at least one two-dimensional fast Fourier transform (para [0118], [0119] and [0123] to [0125]);
determining at least one array data set, which comprises at least the magnitude information and the phase information of the at least one part of the virtual antenna elements; and
feeding at least a part of data of the at least one array data set to at least one neural network, with which at least one position information for the at least one target is determined (para [0125] to [0130]).
Regarding claim 2, as applied to claim 1, Eschbaumer (para [0125]) teaches that at least one direction information is determined, which characterizes a direction of the at least one target relative to the reference system.
Regarding claim 3, as applied to claim 1, Eschbaumer (para [0123]) teaches that the at least one magnitude information and the at least one phase information are realized as complex values.
Regarding claim 4, as applied to claim 1, Eschbaumer (para [0115]) teaches that time information is determined for at least a part of the virtual antenna elements.
Regarding claim 6, as applied to claim 1, Eschbaumer (para [0093]) teaches that an antenna system with the multiple transmit antenna elements and the multiple receiving antenna elements is arranged and operated to create an undersampled system and/or an antenna array with the multiple transmit antenna elements and the multiple receiving antenna elements is arranged and operated to create a sparse virtual antenna array.
Regarding claim 9, as applied to claim 1, Eschbaumer (para [0125] and [0135]) teaches that the at least one neural network is learned by array data sets both from the magnitude information and the phase information.
Claims 10-12 are rejected for having the same scope as claim 1.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 5, 7 and 8 are rejected under 35 U.S.C. 103 as being unpatentable over Eschbaumer.
Regarding claim 5, Eschbaumer teaches the claimed invention, as applied to claim 1, except explicitly mention that the at least one part of the data of the array data set is fed to the at least one neural network designed as a spiking neural network. However, spiking neural network is common technical knowledge to achieve energy efficiency and processing time.
Regarding claim 7, Eschbaumer teaches the claimed invention, as applied to claim 1, except explicitly mention that four most distant virtual antenna elements are arranged at corners of a rectangle whose side lengths each correspond to integer multiples of half of a wavelength of the radar signals, and at least one additional virtual antenna element is arranged at a distance of approximately the half of the wavelength of the radar signals from one of the four most distant virtual antenna elements. However, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to arrange the four most distant virtual antenna elements at corners of a rectangle whose side lengths each correspond to integer multiples of half of a wavelength of the radar signals, and at least one additional virtual antenna element is arranged at a distance of approximately the half of the wavelength of the radar signals from one of the four most distant virtual antenna elements in order to maximize the effective aperture size along both azimuth and elevation axes while keeping the total number of physical antennas low in MIMO radar systems, since it has been held that rearranging parts of an invention involves only routine skill in the art. In re Japikse, 86 USP 70.
Regarding claim 8, Eschbaumer teaches the claimed invention, as applied to claim 1, except explicitly mention that a two-step learning technique is applied for learning the at least one neural network. However, dividing the process into two smaller parts instead of training a neural network all at once is common knowledge in the art to improve model convergence and boost accuracy.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Sturm (DE 102020125323 A1) discloses method of operating a radar system.
Teplitsky et al (WO 2022/139844 A1) discloses a method of operating a radar system.
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/HOANG V NGUYEN/Primary Examiner, Art Unit 2845
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