Abstract: A hidden chamber detector includes a linear frequency modulated continuous wave (LFMCW) radar, a synthetic aperture radar (SAR) imaging processor, and a time division multiple access (TDMA) multiple input multiple output (MIMO) antenna array, including a plurality of transmitting and receiving (Tx-Rx) antenna pairs. A Tx-Rx antenna pair is selected, in a time division manner, as a Tx antenna and an Rx antenna for the LFMCW radar. The LFMCW radar is configured to transmit an illumination signal, receive an echo signal, convert the echo signal to a baseband signal, collect baseband samples, and send the collected samples to the SAR imaging processor. The SAR imaging processor is configured to receive the collected samples, collect structure/configuration of the antenna array and scanning information, and form an SAR image based on the collected samples, the structure/configuration of the antenna array, and the scanning information.

Abstract: An apparatus includes a camera for capturing an image at a first moment; a range finder for measuring a distance to an object at a center of the image; a rotatable mounting platform, fixedly hosting the camera and the range finder; and a controller. The controller is configured to receive the captured image and the measured distance; determine whether a target of interest (TOI) appears in the image; in response to determining a TOI appearing in the image, determine whether the TOI appears at the center of the image; calculate position parameters of the rotatable mounting platform for centering the TOI in an image to be captured at a second moment, separated from the first moment by a pre-determined time interval; control the rotatable mounting platform to rotate according to the calculated position parameters; and calculate and store the position parameters of the TOI with respect to the apparatus.

Abstract: A hidden chamber detector includes a linear frequency modulated continuous wave (LFMCW) radar, a synthetic aperture radar (SAR) imaging processor, and a time division multiple access (TDMA) multiple input multiple output (MIMO) antenna array, including a plurality of transmitting and receiving (Tx-Rx) antenna pairs. A Tx-Rx antenna pair is selected, in a time division manner, as a Tx antenna and an Rx antenna for the LFMCW radar. The LFMCW radar is configured to transmit an illumination signal, receive an echo signal, convert the echo signal to a baseband signal, collect baseband samples, and send the collected samples to the SAR imaging processor. The SAR imaging processor is configured to receive the collected samples, collect structure/configuration of the antenna array and scanning information, and form an SAR image based on the collected samples, the structure/configuration of the antenna array, and the scanning information.

Abstract: A biological sample image collection device (100), comprising support (30) and an optical imaging assembly (50), also comprises: a plurality of movable platforms (40), for placing biological samples (20) wherein the plurality of movable platforms (40) are arranged on the support (30) in an array; the plurality of movable platforms (40) can move relative to the support (30); and forces acting on the support (30) during the movement of the movable platforms can cancel each other out, so as to avoid vibrations affecting the support (30) and the biological samples (20) are canceled. The optical imaging assembly (50) collects images of the biological samples (20) on the movable platforms (40) when the plurality of movable platforms (40) move, relative to the center of the array, in the same direction and at the same speed. Further provided is a gene sequencer including the biological sample image collection device (100).

Abstract: A scheduling system includes a receiving system and a transfer system. The receiving system receives a carrier carrying a biological sample. The transfer system transfers the sample carrier between biochemical reaction platform and detection platform, so that a sample in the sample carrier performs a biochemical reaction on the biochemical reaction platform, and a signal from the reacted sample can be detected on the detection platform. The present disclosure further provides a scheduling method, a scheduling control system, a biochemical analysis system and device, and a computer-readable storage medium. The present disclosure improves a degree of automation of sample carrier scheduling, and realizes simultaneous analysis of multiple sample carriers to improve a testing throughput.

Abstract: A biochemical substance analysis system (5) is used to detect biological characteristics of a sample in a flow cell (38), and includes a detection system (51), a scheduling system (53), a biochemical reaction system (55). and a control system (57). The scheduling system (53) is used to schedule the flow cell (38) at different sites, including sites in the detection system (51) and sites in the biochemical reaction system (55). The biochemical reaction system (55) is used to allow the sample to react in the flow cell (38). The detection system (51) is used to detect a signal from the reacted sample to obtain a signal representing the biological characteristics of the sample. The control system (57) is used to control the detection system (51), the scheduling system (53), and the biochemical reaction system (55) to cooperate. The disclosure improves automation degree and flux of the biochemical substance analysis.

Abstract: The present disclosure provides a method for joint manifold learning based heterogenous sensor data fusion, comprising: obtaining learning heterogeneous sensor data from a plurality sensors to form a joint manifold, wherein the plurality sensors include different types of sensors that detect different characteristics of targeting objects; performing, using a hardware processor, a plurality of manifold learning algorithms to process the joint manifold to obtain raw manifold learning results, wherein a dimension of the manifold learning results is less than a dimension of the joint manifold; processing the raw manifold learning results to obtain intrinsic parameters of the targeting objects; evaluating the multiple manifold learning algorithms based on the raw manifold learning results and the intrinsic parameters to determine one or more optimum manifold learning algorithms; and applying the one or more optimum manifold learning algorithms to fuse heterogeneous sensor data generated by the plurality sensors.

Abstract: An apparatus includes a camera for capturing an image at a first moment; a range finder for measuring a distance to an object at a center of the image; a rotatable mounting platform, fixedly hosting the camera and the range finder; and a controller. The controller is configured to receive the captured image and the measured distance; determine whether a target of interest (TOI) appears in the image; in response to determining a TOI appearing in the image, determine whether the TOI appears at the center of the image; calculate position parameters of the rotatable mounting platform for centering the TOI in an image to be captured at a second moment, separated from the first moment by a pre-determined time interval; control the rotatable mounting platform to rotate according to the calculated position parameters; and calculate and store the position parameters of the TOI with respect to the apparatus.

Abstract: A multiple-input and multiple-output (MIMO) bolt-on device for a single-input and single-output (SISO) radio, a MIMO channel emulator for testing the MIMO bolt-on device, and a MIMO channel emulation method are provided. The MIMO bolt-on device includes: a plurality of antennas, a multi-channel receiver, a plurality of couplers, a micro-controller, and a switch device. The multi-channel receiver includes a plurality of channels for signal transmission. Each coupler is configured to couple the multi-channel receiver with one of the plurality of antennas. The micro-controller is coupled to the multi-channel receiver to compare signals from the plurality of channels, thereby identifying a channel with a highest signal-to-noise (SNR) among the plurality of channels. The switch device is coupled to the micro-controller and configured to select an antenna corresponding to the channel with the highest SNR among the plurality of antennas for a connection between a selected antenna and the SISO radio.

Abstract: A multiple-input and multiple-output (MIMO) bolt-on device for a single-input and single-output (SISO) radio, a MIMO channel emulator for testing the MIMO bolt-on device, and a MIMO channel emulation method are provided. The MIMO bolt-on device includes: a plurality of antennas, a multi-channel receiver, a plurality of couplers, a micro-controller, and a switch device. The multi-channel receiver includes a plurality of channels for signal transmission. Each coupler is configured to couple the multi-channel receiver with one of the plurality of antennas. The micro-controller is coupled to the multi-channel receiver to compare signals from the plurality of channels, thereby identifying a channel with a highest signal-to-noise (SNR) among the plurality of channels. The switch device is coupled to the micro-controller and configured to select an antenna corresponding to the channel with the highest SNR among the plurality of antennas for a connection between a selected antenna and the SISO radio.

Abstract: A framework for estimating image interpretability degradation associated with image compression is provided. An image compression broker system can determine an image compression setting to achieve an interpretability task in accordance with available communication bandwidth or transmission time objectives. Estimating image interpretability degradation includes detecting edge points of an uncompressed image and determining gradients corresponding to the detected edge points; compressing in accordance with a compression parameter setting the uncompressed image to generate a compressed image and determining gradients corresponding to the edge points in the compressed image; determining from the gradients associated with the edge points gradient ratios; and estimating from the gradient ratios an image interpretability loss of the compressed image.

Abstract: A multiple-input and multiple-output (MIMO) bolt-on device for a single-input and single-output (SISO) radio, a MIMO channel emulator for testing the MIMO bolt-on device, and a MIMO channel emulation method are provided. The MIMO bolt-on device includes: a plurality of antennas, a multi-channel receiver, a plurality of couplers, a micro-controller, and a switch device. The multi-channel receiver includes a plurality of channels for signal transmission. Each coupler is configured to couple the multi-channel receiver with one of the plurality of antennas. The micro-controller is coupled to the multi-channel receiver to compare signals from the plurality of channels, thereby identifying a channel with a highest signal-to-noise (SNR) among the plurality of channels. The switch device is coupled to the micro-controller and configured to select an antenna corresponding to the channel with the highest SNR among the plurality of antennas for a connection between a selected antenna and the SISO radio.

Abstract: A multiple-input and multiple-output (MIMO) bolt-on device for a single-input and single-output (SISO) radio, a MIMO channel emulator for testing the MIMO bolt-on device, and a MIMO channel emulation method are provided. The MIMO bolt-on device includes: a plurality of antennas, a multi-channel receiver, a plurality of couplers, a micro-controller, and a switch device. The multi-channel receiver includes a plurality of channels for signal transmission. Each coupler is configured to couple the multi-channel receiver with one of the plurality of antennas. The micro-controller is coupled to the multi-channel receiver to compare signals from the plurality of channels, thereby identifying a channel with a highest signal-to-noise (SNR) among the plurality of channels. The switch device is coupled to the micro-controller and configured to select an antenna corresponding to the channel with the highest SNR among the plurality of antennas for a connection between a selected antenna and the SISO radio.

Abstract: A method for testing satellite signal receiver antenna is provided. The method includes: determining a satellite constellation state indicating status of a plurality of satellites in a satellite constellation; calculating, based on the determined satellite constellation state, initial positions of a plurality of satellite antennas that are used for emulating the satellite constellation; moving the plurality of satellite antennas to the initial positions of the plurality of satellite antennas; calibrating a phase delay of each of the plurality of satellite antennas; broadcasting, by the plurality of satellite antennas, satellite signals to test a satellite signal receiver antenna; determining a movement plan for the plurality of satellite antennas based on the satellite constellation state; and moving the plurality of satellite antennas based on the movement plan to emulate a propagation of the satellite constellation.

Abstract: A cone-based multi-layer wide band antenna is provided, including a cone-based member having a multi-layer structure. The multi-layer structure includes a first layer conical structure, and the first layer conical structure has a height and a base radius configured to provide a desired impedance of the antenna.

Abstract: A cone-based multi-layer wide band antenna is provided, including a cone-based member having a multi-layer structure. The multi-layer structure includes a first layer conical structure, and the first layer conical structure has a height and a base radius configured to provide a desired impedance of the antenna.

Abstract: The present disclosure provides a method for joint manifold learning based heterogenous sensor data fusion, comprising: obtaining learning heterogeneous sensor data from a plurality sensors to form a joint manifold, wherein the plurality sensors include different types of sensors that detect different characteristics of targeting objects; performing, using a hardware processor, a plurality of manifold learning algorithms to process the joint manifold to obtain raw manifold learning results, wherein a dimension of the manifold learning results is less than a dimension of the joint manifold; processing the raw manifold learning results to obtain intrinsic parameters of the targeting objects; evaluating the multiple manifold learning algorithms based on the raw manifold learning results and the intrinsic parameters to determine one or more optimum manifold learning algorithms; and applying the one or more optimum manifold learning algorithms to fuse heterogeneous sensor data generated by the plurality sensors.

Abstract: A method for testing satellite signal receiver antenna is provided. The method includes: determining a satellite constellation state indicating status of a plurality of satellites in a satellite constellation; calculating, based on the determined satellite constellation state, initial positions of a plurality of satellite antennas that are used for emulating the satellite constellation; moving the plurality of satellite antennas to the initial positions of the plurality of satellite antennas; calibrating a phase delay of each of the plurality of satellite antennas; broadcasting, by the plurality of satellite antennas, satellite signals to test a satellite signal receiver antenna; determining a movement plan for the plurality of satellite antennas based on the satellite constellation state; and moving the plurality of satellite antennas based on the movement plan to emulate a propagation of the satellite constellation.

Abstract: The present disclosure provides a gated range scanning linear frequency modulated continuous wave (LFMCW) radar structure, including: a frequency synthesizer, a first mixer, a second mixer, a first filter, and a third mixer. The frequency synthesizer is configured for generating a first local oscillating signal and a second local oscillating signal, a frequency of the first local oscillating signal varying in a frequency range, each frequency corresponding to a sub-range of a coverage range scanned by the LFMCW radar structure. The first mixer is configured for mixing a copy of a transmitted signal and the first local oscillating signal to generate a first output signal (the receiver's first local oscillator). The second mixer is configured for mixing the first output signal and a received signal from a receiving antenna to generate a second output signal that includes an intermediate frequency (IF) signal being received by the first filter.

Abstract: A systematic interferences mitigation design for protected satellite communications (SATCOM) is provided. An advanced channel coding is designed to provide coding gain for SATCOM even in the presence of synchronization errors because of unintentional and intentional radio frequency interferences (RFIs). A unified SATCOM system spectrum efficiency and energy efficiency performance model is developed with a unified interference model for SATCOM dynamic resource allocation (DRA). The SATCOM system DRA is designed with a game theoretic engine and link optimizations providing traffic control, power control, frequency hopping pattern selection, beamforming codebook selection, and modulation with coding agile waveform adaptations. The interferences mitigation design is implemented with software defined radio USRP and GNU-radio to maintain communication link quality of services (QoS).