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
Claims 1-2, 6-7, 14-15 are rejected under 35 USC 102(a)(1) as being unpatentable over Findlay et al. US 2018/0040222.
As to claim 1, Findlay teaches a device comprising: two matched antennas configured to transmit and receive ultra-wideband, UWB signals (esp. c.f. [0014, 0030] teaching UWB signals), an electronic circuit coupled to the matched antennas (esp. c.f. fig.4), the electronic circuit comprising a microprocessor configured to process the received UWB signals and to measure a channel impulse response (esp. c.f. [0068] teaching processing the signals and measuring the response), between a transmitter channel and a receiver channel of the electronic circuit (see fig.3 and [0067] teaching transmitter and receiver channels of the circuit), the microprocessor further configured to convert a time between a transmission of the UWB signals and a receipt of the UWB signals into a distance (esp. c.f. [0066-0067] teaching converting the time between the transmission signals), and the electronic circuit being further configured to detect a target and/or estimate a distance from the device to the target and/or track the target and/or track a distance of the target from the device and/or track a velocity of the target based on the processed UWB signals (see figs. 6-7 and [0062] teaching tracking of the target from the device); and an alarm unit configured to receive, from the machine learning unit, information on the detected target, the information comprising a measurement of CIR confidence intervals and an adaptive threshold (see fig.6 and [0008] teaching alarm unit that cooperates with target detection mechanisms).
As to claim 2, Findlay teaches the device as claimed in claim 1, further comprising a machine learning unit coupled to the electronic circuit, wherein the machine learning unit comprises a processor and a memory (esp. c.f. [0043, 0057, 0060] teaching machine learning unit with processor and memory), wherein the machine learning unit is configured to detect the target, classify the target, and declare an alarm based on the received UWB signals (see fig.5, [[073, 0083] teaching classifying target and communicating with alarm based on signaling), the machine learning unit further comprising a machine learning algorithm stored in the memory, wherein the machine learning algorithm is configured to detect of the target, classify the target and the declare the alarm (esp. c.f. [0083, 0085-0086] teaching algorithm stored in memory to detect target and communicate with the unit based on the signaling).
As to claim 6, Findlay teaches the device of claim 1, further comprising a 3-dimensional system configured to estimate a height of the detected target based on information received from the transmitter channel and/or the receiver channel of the electronic circuit (see fig.3 and [0067]).
As to claim 7, Findlay teaches the device as claimed in claim 2 wherein the machine learning unit is configured to determine a position and/or detected target size and/or direction of movement and/or velocity of the detected target, and/or metal object being carried by the detected target, based on the processed UWB signals (see figs. 6-7 and [0062] teaching tracking of the target from the device).
As to claim 14, Findlay teaches a device comprising: matched antennas specifically to penetrate various surfaces and to transmit and receive signals through structures (esp. c.f. [0014, 0030] teaching UWB signals), an electronic circuit coupled to the matched antennas (esp. c.f. fig.4), the electronic circuit comprising a microprocessor configured to process the received UWB signals and to measure a channel impulse response (esp. c.f. [0068] teaching processing the signals and measuring the response), between a transmitter channel and a receiver channel of the electronic circuit (see fig.3 and [0067] teaching transmitter and receiver channels of the circuit), the microprocessor further configured to convert a time between a transmission of the UWB signals and a receipt of the UWB signals into a distance (esp. c.f. [0066-0067] teaching converting the time between the transmission signals), and the electronic circuit being further configured to detect a target and/or estimate a distance from the device to the target and/or track the target and/or track a distance of the target from the device and/or track a velocity of the target based on the processed UWB signals (see figs. 6-7 and [0062] teaching tracking of the target from the device); and an alarm unit configured to receive, from the machine learning unit, information on the detected target, the information comprising a measurement of CIR confidence intervals and an adaptive threshold (see fig.6 and [0008] teaching alarm unit that cooperates with target detection mechanisms).
As to claim 15, Findlay teaches a device comprising: a transmitter and receiver configured to transmit/receive UWB signals (esp. c.f. [0014, 0030] teaching UWB signals), an electronic circuit coupled to the matched antennas (esp. c.f. fig.4), the electronic circuit comprising a microprocessor configured to process the received UWB signals and to measure a channel impulse response (esp. c.f. [0068] teaching processing the signals and measuring the response), between a transmitter channel and a receiver channel of the electronic circuit (see fig.3 and [0067] teaching transmitter and receiver channels of the circuit), the microprocessor further configured to convert a time between a transmission of the UWB signals and a receipt of the UWB signals into a distance (esp. c.f. [0066-0067] teaching converting the time between the transmission signals), and the electronic circuit being further configured to detect a target and/or estimate a distance from the device to the target and/or track the target and/or track a distance of the target from the device and/or track a velocity of the target based on the processed UWB signals (see figs. 6-7 and [0062] teaching tracking of the target from the device); and an alarm unit configured to receive, from the machine learning unit, information on the detected target, the information comprising a measurement of CIR confidence intervals and an adaptive threshold (see fig.6 and [0008] teaching alarm unit that cooperates with target detection mechanisms).
Claim Objections
Claims 3-5 and 8-13 are objected to for depending upon rejected base claims but would otherwise be allowable.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Bo Fan whose telephone number is (571)-272-3013. The examiner can normally be reached on M-F from 9AM to 5:30PM.
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/Bo Fan/
Examiner, Art Unit 3646
Prosecution Insights