Method and device for detecting and / or recognizing objects

Abstract

Aspects of the subject disclosure may include, for example, creating a first sequence of optical signals based on a first sequence of electrical signals, the first sequence of electrical signals associated with a plurality of matched filters, directing the first sequence of optical signals to a plurality of objects, receiving a second sequence of optical signals based on reflections of the first sequence of optical signals on the plurality of objects, converting the second optical signal sequence into a second electrical signal sequence, processing the second electrical signal sequence according to a plurality of matched filters to extract information associated with a plurality of objects, adjusting the first electrical signal sequence into a third electrical signal sequence, adjusting the plurality of matched filters according to the third electrical signal sequence, an adjusted sequence of optical signals is generated from the third sequence of electrical signals, and the adjusted sequence of optical signals is directed to further improve extraction information associated with the plurality of objects. Other embodiments are also disclosed.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to U.S. Patent Application Serial No. 18 / 313,885 filed on May 8, 2023, which claims priority to U.S. Provisional Patent Application Serial No. 63 / 425,502 filed on November 15, 2022. All portions of the above applications are incorporated herein by reference in their entirety. Technical Field

[0003] The subject disclosure relates to methods and apparatus for detecting and / or identifying objects. Background Art

[0004] Light Detection and Ranging (LiDAR) is a technology by which a light signal, usually in the infrared, is sent into a medium and the reflected light is captured and used to determine the characteristics of the medium. In the most common example, light is sent into free space (air) and the reflected light is captured to determine the distance to the reflecting object. In some implementations, the velocity of the detected object can also be recovered.

[0005] Depending on the application, the requirements for ranging and speed detection may vary significantly. For example, LiDAR is often used for aerial terrain mapping (Secord, J. and Zakhor, A., 2007. Tree detection in urban regions using aerial lidar and image data. IEEE Geoscience and Remote Sensing Letters, 4 (2), pp. 196-200.), where a ranging resolution of less than 1 m is sufficient, although the ranging occurs at distances up to 10 km. For automotive applications, a resolution of 1 cm is acceptable, with a typical maximum distance of 300 m (Royo, S. and Ballesta-Garcia, M., 2019. An overview of lidar imaging systems for autonomous vehicles. Applied sciences, 9 (19), p. 4093.3). LiDAR can also be used for precision metrology, similar to a known medical imaging technique called optical coherence tomography. In these cases, a resolution of 10 μm is required (Shimizu, Y., Chen, LC, Kim, DW, Chen, X., Li, X. and Matsukuma, H., 2021. An insight into optical metrology in manufacturing. Measurement Science and Technology, 32(4), p.042003.). In many of these cases, resolution and range depend on the signal-to-noise ratio (SNR), which can usually be increased by increasing the emitted laser power within eye and skin safety limits.

[0006] Figure 1 A list of various classifications of LiDAR technologies is shown. In scanning LiDAR, mechanical or non-mechanical steering elements direct light to various points in a scene known as a point cloud where ranging and velocity information is obtained on a point-by-point basis. In non-scanning (flash) LiDAR, the entire scene is illuminated with light and then a multi-pixel detector is used to retrieve information from the scene. In many implementations, scanning LiDAR is also used with a multi-element detector array. In addition to the various scanning methods, the transmission and detection methods are also different. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] Reference will now be made to the accompanying drawings, which are not necessarily drawn to scale, and in which:

[0008] Figure 1is a block diagram illustrating an exemplary, non-limiting embodiment of various LiDAR technologies and architectures according to various aspects described herein. See Hsu, CP, Li, B., Solano-Rivas, B., Gohil, A. R., Chan, PH, Moore, A. D. and Donzella, V., 2020. A review and perspective on optical phased array for automotive LiDAR. IEEE Journal of Selected Topics in Quantum Electronics, 27(1), pp. 1-16.

[0009] Figure 2 is a block diagram illustrating an exemplary non-limiting embodiment of FMCW technology for ranging according to various aspects described herein. See Adany, P., Allen, C. and Hui, R., 2009. Chirped lidar using simplified homodyne detection. Journal of lightwave technology, 27(16), pp.3351-3357.

[0010] Figure 3 is a block diagram showing an exemplary non-limiting embodiment of AMCW matched filtering for LiDAR ranging according to various aspects described herein. See Yu, Y., Liu, B. and Chen, Z., 2019. Improving the performance of pseudo-random single-photon counting ranging lidar. Sensors, 19(16), p.3620.

[0011] Figure 4 is a block diagram illustrating an exemplary non-limiting embodiment of a classical modulated LiDAR system in accordance with various aspects described herein.

[0012] Figure 5 is a block diagram illustrating an exemplary non-limiting embodiment demonstrating an adaptive transmitter and receiver system in accordance with various aspects described herein, wherein information from a receiver is passed to a processor which then updates the transmit and receive blocks.

[0013] Figure 6 is a block diagram illustrating an exemplary non-limiting embodiment demonstrating fixed symbol length power reallocation for a sequence in accordance with various aspects described herein.

[0014] Figure 7 is a block diagram illustrating an exemplary non-limiting embodiment according to various aspects described herein, which demonstrates an adaptive symbol sequence change that ensures that the P 0 The observer at P cannot learn the symbol sequence and deceive P i Measurement at.

[0015] Figure 8 is a block diagram illustrating an example non-limiting embodiment demonstrating techniques for updating a transmit sequence and matched filter taps to exclude reflected light from an ambiguity range in accordance with various aspects described herein.

[0016] Fig. 9 is a diagram showing a method for improving the point P according to various aspects described herein. 0 Block diagram of an example non-limiting embodiment of an adaptive acquisition time for ranging performance.

[0017] Fig.10 is a block diagram illustrating an exemplary non-limiting embodiment of a LiDAR system using a digital ASIC, fast feedback, and matched filtering. Note that many other steps and sub-steps may be included or removed from the flow shown above in accordance with various aspects described herein.

[0018] Fig.11 is a block diagram of an exemplary, non-limiting embodiment of a communication device in accordance with various aspects described herein. DETAILED DESCRIPTION

[0019] The subject disclosure describes, among other things, illustrative embodiments for object detection and / or recognition systems. Other embodiments are described in the subject disclosure.

[0020] One or more aspects of the subject disclosure include a method for creating a first sequence of optical signals based on a first sequence of electrical signals provided to a continuous wave (CW) light source, the first sequence of electrical signals being associated with a plurality of matched filters; directing the first sequence of optical signals to a plurality of objects; receiving a second sequence of optical signals based on reflections of the first sequence of optical signals on the plurality of objects; converting the second sequence of optical signals into a second sequence of electrical signals; processing the second sequence of electrical signals according to the plurality of matched filters to extract information associated with the plurality of objects; adjusting the first sequence of electrical signals to a third sequence of electrical signals; adjusting the plurality of matched filters according to the third sequence of electrical signals; applying the third sequence of electrical signals to the CW light source to produce an adjusted sequence of optical signals; and directing the adjusted sequence of optical signals to further improve the extracted information associated with the plurality of objects.

[0021] In one embodiment, adjusting the first electrical signal sequence to a third electrical signal sequence is based on the extracted information. In one embodiment, adjusting a plurality of matched filters according to the third electrical signal sequence is based on the extracted information. In one embodiment, after completing the first optical signal sequence, directing the adjusted optical signal sequence to a plurality of objects.

[0022] In one embodiment, the transmission of the adjusted sequence of optical signals based on the extracted information occurs within a period of time during which the second sequence of optical signals is received. In one embodiment, the period of time is less than 100 microseconds. In one embodiment, the period of time is less than 10 times the round trip time of light reflected from the plurality of objects. In one embodiment, the length of the first sequence of electrical signals is greater than the period of time.

[0023] In one embodiment, the information rate of the first or second electrical signal sequence has a bit rate greater than 20 gigabits per second. In one embodiment, the pattern length of the first electrical signal sequence is greater than 1000 symbols. In one embodiment, the symbol interval of the first electrical signal is less than 50 picoseconds. In one embodiment, the process of extracting information is substantially nonlinear. In one embodiment, the third electrical signal sequence and the first and second electrical signal sequences are located in a single integrated circuit. In one embodiment, the symbol sequences in the first and third electrical signal sequences consist of periodic symbol sequences. In one embodiment, the symbol sequences in the first and third electrical signal sequences consist of different symbol sequences. In one embodiment, the symbol sequences in the first and third electrical signal sequences are substantially orthogonal. In one embodiment, the first optical signal sequence and the adjusted optical signal sequence are generated from a CW light source, and wherein the first and third electrical signal sequences are generated by electro-optical modulation.

[0024] In one embodiment, the energy bandwidth associated with the first, second and third electrical signal sequences is greater than 10 GHz. In one embodiment, the first, second and third electrical signal sequences are composed of different subcarriers carrying related or independent sequences or subsequences, which are then processed by multiple matched filters. In one embodiment, the first, second and third electrical signal sequences are composed of different wavelengths carrying related or independent sequences or subsequences, which are then processed by multiple matched filters. In one embodiment, the first and second optical signal sequences and the adjusted optical signal sequence are propagated through the air. In one embodiment, converting the second optical signal sequence into the second electrical signal sequence is performed by a detector having a bandwidth greater than 50 GHz. In one embodiment, the conversion of the second optical signal sequence to the second electrical signal sequence is performed using an intensity detector.

[0025] In one embodiment, the conversion of the second optical signal sequence into the second electrical signal sequence is performed using a coherent detector. In one embodiment, the coherent detector uses a portion of the CW light source as a local oscillator. In one embodiment, the coherent detector uses another CW light source as a local oscillator.

[0026] In one embodiment, the processing of the second electrical signal sequence includes performing analog-to-digital conversion. In one embodiment, the processing of the second electrical signal sequence includes performing digital signal processing. In one embodiment, at least a portion of the digital signal processing is performed in an application specific integrated circuit (ASIC) or a field programmable gate array (FPGA). In one embodiment, the processing includes correlating the first and second electrical signal sequences using a fixed length matched filter. In one embodiment, the extracted information includes absorption (magnitude), delay (phase), orientation (polarization (or polarization)) or a combination thereof. In one embodiment, the extracted information is used to determine features of multiple objects, the features including distance, speed, signal-to-noise ratio (SNR) or a combination thereof. In one embodiment, a symbol sequence associated with a third electrical signal sequence is generated based on at least a portion of the extracted information.

[0027] In one embodiment, the third electrical signal sequence is composed of a symbol sequence having different electrical power relative to other sequences associated with the first electrical signal sequence. In one embodiment, the third electrical signal sequence is composed of a symbol sequence orthogonal to other symbol sequences associated with the first electrical signal sequence. In one embodiment, the first symbol rate of the first electrical signal sequence is different from the third symbol rate associated with the third electrical signal sequence. In one embodiment, the total length of the first number of symbols of the first electrical signal sequence is different from the third number of symbols associated with the third electrical signal sequence. In one embodiment, the first length of the first orthogonal sequence of the first electrical signal sequence is different from the third length of the third orthogonal sequence associated with the third electrical signal sequence. In one embodiment, the taps in the multiple matched filters used for correlation are suitable for iteratively matching the first electrical signal sequence, the third electrical signal sequence, or a combination thereof.

[0028] One or more aspects of the subject disclosure include an apparatus that may include a processing system that includes a processor and a memory storing executable instructions that, when executed by the processing system, facilitate the performance of operations. The operations may include creating a first sequence of optical signals based on a first sequence of electrical signals provided to a continuous wave (CW) light source, the first sequence of electrical signals being associated with a plurality of matched filters; directing the first sequence of optical signals to a plurality of objects; receiving a second sequence of optical signals based on reflections of the first sequence of optical signals on the plurality of objects; converting the second sequence of optical signals into a second sequence of electrical signals; processing the second sequence of electrical signals according to the plurality of matched filters to extract information associated with the plurality of objects; adjusting the first sequence of electrical signals to a third sequence of electrical signals; adjusting the plurality of matched filters according to the third sequence of electrical signals; applying the third sequence of electrical signals to the CW light source to produce an adjusted sequence of optical signals; and directing the adjusted sequence of optical signals to further improve the extracted information associated with the plurality of objects.

[0029] One or more aspects of the subject disclosure include a machine-readable medium that may include executable instructions that, when executed by a processing system including a processor, facilitate the performance of operations. The operations may include creating a first sequence of optical signals based on a first sequence of electrical signals provided to a continuous wave (CW) light source, the first sequence of electrical signals being associated with a plurality of matched filters; directing the first sequence of optical signals to a plurality of objects; receiving a second sequence of optical signals based on reflections of the first sequence of optical signals on the plurality of objects; converting the second sequence of optical signals into a second sequence of electrical signals; processing the second sequence of electrical signals according to the plurality of matched filters to extract information associated with the plurality of objects; adjusting the first sequence of electrical signals to a third sequence of electrical signals; adjusting the plurality of matched filters according to the third sequence of electrical signals; applying the third sequence of electrical signals to the CW light source to produce an adjusted sequence of optical signals; and directing the adjusted sequence of optical signals to further improve the extracted information associated with the plurality of objects.

[0030] Time of Flight (ToF) Direct Detection

[0031] Distance information is derived through a scene by measuring the time of flight (ToF) of a laser pulse after it reflects from an object. A pulsed laser, which can emit pulses with a period of microseconds, is detected incoherently (intensity detection). Typically, multiple measurements must be made to determine an accurate distance measurement due to the poor receiver sensitivity of direct detection. This can be accomplished by histogramming the ToF using a time-to-digital converter (TDC), a photomultiplier tube (PMT), or a time-correlated single photon counter (TC-SPC).

[0032] One downside of pulsed laser transmission is that there is a limited ambiguity range. Simply put, the transmitted pulses need to be spaced far enough apart so that there is no ambiguity in receiving the reflected pulses, otherwise there may be significant errors in the distance measurement. With ToF methods based on direct detection, multiple measurements may be required to determine the speed of the detected object.

[0033] Frequency Modulated Continuous Wave (FMCW)

[0034] Frequency modulated continuous wave (FMCW) technology is a coherent technique in which a laser is swept and then coherently combines with a local copy of itself after reflecting from a target, such as Figure 2 As shown. Since the frequency of the light source is time-dependent, the frequency difference between the transmitted field and the local field in the coherent receiver is directly converted into the distance of the object, which is usually measured in the frequency domain via Fourier transform. In addition, by measuring the entire frequency range of the received optical waveform, the speed of the object being measured can be detected. The magnitude and sign of the frequency shift (caused by the Doppler effect) can be used to determine the speed of the object.

[0035] FMCW light sources can be specially designed lasers (such as those used in optical coherence tomography), or they can be digitally chirped. Typical values ​​for chirp rates are on the order of 10-100 MHz per microsecond. Coherent detection schemes for FMCW typically utilize a single orthogonal homodyne coherent detector, although dual orthogonal coherent detectors can be used.

[0036] Pseudo-random modulated continuous wave (PRMCW) LiDAR

[0037] PRMCW LiDAR relies on direct or external modulation of an optical signal that is sent to the scene and then received in a coherent or incoherent receiver. Typically, the modulated signal is correlated with a local copy of itself (known as matched filtering) in order to improve the SNR of the ranging measurement. Figure 3 This technique is shown for AMCW transmission and non-coherent detection.

[0038] Sequence length

[0039] The length of the sequence being sent is important. The length is the number of symbols (also called chips) in the pattern that are sent before the pattern repeats. In a pulsating system, the length is one symbol (plus the dead time between pulses). As described below, the desired sequence pattern can be repeatedly selected and sent.

[0040] Assuming that consecutive sequences are identical, the length of the sequence in seconds, including any dead time, multiplied by the speed of light in the medium, equals the round-trip ambiguity distance. Longer sequences can eliminate the need for dead time. Longer sequences can provide better suppression of uncorrelated interference. The duration of one symbol (chip time) strongly determines the range resolution. Therefore, the number of symbols in the sequence is important.

[0041] Amplitude Modulated Continuous Wave (AMCW)

[0042] AMCW is a modulated LiDAR technique derived from RADAR technology, where the light signal is modulated with a known waveform and correlated with itself after reception. This technique can be used in a flash LiDAR configuration, where a multi-pixel detector is then able to reconstruct the illuminated scene based on the temporal correlation between different pixels. AMCW is often used in conjunction with incoherent detection techniques.

[0043] Random Amplitude Modulated Continuous Wave (RAMCW)

[0044] RAMCW differs from AMCW in that the modulation waveform is selected from a class of orthogonal or pseudo-orthogonal random sequences. Some embodiments use a raw pseudo-random binary sequence (PRBS) stream, a maximum length sequence (MLS), a Golay complementary pair, a Legendre sequence, or an A* sequence. The selected sequence is selected to have excellent autocorrelation properties. In other words, they have high suppression of noise and other sequences. As in AMCW, incoherent detection is typically used to digitize the waveform or perform a histogram analysis on the waveform, after which the sequence is correlated with a local copy to determine the range. Importantly, relative object motion (which introduces Doppler shift) or other time phase effects (such as laser line width) can degrade the matched filtering in the receiver and lead to erroneous ranging. Incoherent detection of AMCW signals may not be able to estimate the velocity of the object being ranged.

[0045] Coherent Random Amplitude Modulated Continuous Wave (Coherent RAMCW)

[0046] Instead of using non-coherent detection, coherent detection can also be used to receive the transmitted waveform. Typically, this is achieved using dual-orthogonal coherent detection in order to estimate the relative phase of the received signal compared to the local oscillator. Dual-orthogonal coherent receivers can be heterodyne or homodyne. In this case, after digitization, the time phase effects can be corrected before matched filtering to ensure accurate ranging and velocity estimates.

[0047] Local processing

[0048] In some embodiments of LIDAR applications, the latency due to offline processing is acceptable. The geographic separation between the receiver and the processor sets a lower limit on this latency. The amount of data received in one scan and the transmission capacity to the processor creates another source of latency. (In digital systems, this is bits per scan and bits per second; the ratio is per scan second) For example, if the distance from the receiver to the processor and then to the transmitter is 100 km, and optical fiber is used for the connection, the latency due to the speed of light in glass is about 500 microseconds.

[0049] When the receiver is mobile or hidden, the transmission capacity may be very limited, resulting in long latency when sending data. Degradation of this transmission (or transmission) may result in significantly long latency. There may be applications where such latency is unacceptable. One attempt to alleviate this problem is to reduce the transmission bottleneck by compressing the information in the point cloud locally.

[0050] Real-time processing

[0051] When the medium is not static, adaptive detection may not tolerate the latency caused by offline processing. Real-time decisions made at the receiver site may not tolerate this latency. For example, braking or steering an autonomous vehicle.

[0052] For real-time LiDAR systems, such as those intended for use in vehicles, where the captured data cannot be processed offline, there are some limitations on typical matched filtering techniques. In the present subject disclosure, an offline matched filter LiDAR system may be defined as a system that cannot store and output captured waveforms for processing with variable-length, typically long matched filters. Due to the amount of data captured in a real-time LiDAR system, this is a typical constraint on commercial products.

[0053] For LiDAR waveforms to be processed in real time using matched filtering techniques, there are some trade-offs that are usually made. First, the matched filter needs to have a fixed, relatively small length in order to reduce the complexity and power consumption of the matched filter. One problem with this is that it overrides the SNR of the distance measurement for any point in the point cloud. Since a given 2D or 3D point cloud can consist of a wide variety of objects with different ranges, distances, reflectivities, and path losses, it may be more efficient to customize the waveform on a per-point basis.

[0054] Second, matched filters are typically static or pseudo-static. Since the filter is fixed, this means that for the matched filter, the transmitted waveform also needs to be fixed to effectively measure the distance of the object. Fixed waveforms have the following disadvantages: (1) For wide aperture receivers, ambiguous data may be received. In other words, if you send the same orthogonal sequence to every point in the point cloud, and you receive pulses from different locations in the point cloud, you may detect an object at two distances at the same time and cannot distinguish between them; (2) If the sequence sent is the same pulse each time, a malicious actor may be able to learn the sequence and send it back to the receiver at the right time to trick the receiver into incorrectly identifying the object, or conversely, not identifying the object.

[0055] Standard LiDAR modulation scheme

[0056] To illustrate the features of the subject disclosure, we can examine a LiDAR system with the following features:

[0057] The sequence sent from the location represented by P i The points in the point cloud address the reflection of objects within the volume, where the point cloud has N pts

[0058] Addressed as P i The sequence is represented by S i N i All N i Symbols can be combined into a length of N i orthogonal sequences, or these symbols can be divided into <N i Multiple sequences of

[0059] Total sequence period T i By the symbol N i The total number and symbol period Δt i Sure

[0060] At the receiver, a filter is used to extract the ranging information from the transmitted sequence. The filter is represented by W i M i Tap composition

[0061] The total filtering time length is T′ i , and the tap is at Δt′ i Separate

[0062] The embodiments discussed below focus on the use of transmitted sequences and receiver filters that can be adaptively updated and changed to improve one or more aspects of range / velocity measurements. The proposed approach is to use a transmitter / receiver system that can communicate with an external processor (e.g., an FPGA) with very short latency. If the processing time on the processor is short enough, a point-by-point or frame-by-frame decision can be made. Here, point-by-point refers to adaptive changes that process each point in the point cloud separately. Frame-by-frame means that adaptive changes occur only after each point in the point cloud is processed at least once. Adaptive changes can also exist after a subset of points are processed. An example of this is making adaptive changes in a 2D raster scanning system where you process points in one row of the scene and then move to the row above. If a decision can be made quickly to mark an area of ​​interest or disinterest, the system can process points clustered near that area on the next row scan (slower than point-by-point, but faster than frame-by-frame).

[0063] In addition, the following embodiments can be used with or without prior information about the scene. An example of prior information about the scene would be a calibration scan used to determine features about the scene. Adaptive changes can then be made to more accurately track smaller changes. Alternatively, decisions can be made on the first scan of the scene based on immediate feedback. Based on the foregoing embodiments, the processor can be adapted to use an object classification method to determine the region of interest. Object classification can output a subset of points based on the full set or subset of the point cloud data.

[0064] Adaptive transmitter and receiver system

[0065] Figure 5 A diagram illustrating a canonical self-adaptive transmitter and receiver system is shown in .

[0066] Adaptive updating of fixed-length symbol sequences

[0067] Power redistribution

[0068] Using information or feedback about the imaged scene, the transmitter algorithm can decide to i A different symbol sequence is sent. One embodiment is to vary the power of a fixed length symbol sequence based on electronic feedback to increase or decrease the optical power for processing a particular point or subset of points. For example, if the processor indicates that a subset of points has been poorly imaged or has a poor SNR, the symbol sequence power can be increased to compensate for the low SNR, such as Figure 6 This can be achieved in an external electro-optic modulator by transmitting a higher power RF signal to reduce modulator losses. In a direct modulation system, this can be achieved by driving the laser with a higher current. Potential benefits of this approach include improved transmitter / receiver efficiency.

[0069] Symbol sequence and matched filter adaptation (adaptation, also known as "self-adaptation" or "self-adaptation")

[0070] As an alternative, or in combination with one or more of the foregoing embodiments, different points or point clusters may be processed with different symbol sequences. Here, after a certain period of time, the transmitted symbol sequence is changed to a separate orthogonal sequence. At a time that may correspond to the point acquisition time T i After an additional period of time, the matched filter can then be updated to distinguish the symbol sequence corresponding to the newly updated symbol sequence. These embodiments differ from other systems in that the decision regarding the finite length matched filter is made adaptively in real time using a single matched filter. There are at least two possible benefits:

[0071] First, the technique enables a reliable form of LiDAR that is resistant to interference from ambient light (potentially the sun), light from similar LiDAR systems, or target light from malicious actors. In the latter, the receiver can be tricked into predicting an object that is not there, or alternatively, into blurring the object. In a typical real-time modulation receiver implementation, a fixed transmitter sequence and matched filters would be used, which are predictable. By rapidly and randomly changing the symbol sequence, the receiver ensures that the received pulses are locally generated. This is in Figure 7 Shown in.

[0072] Second, the method can improve the spatial discrimination of LiDAR systems that may capture reflected light from multiple points in a point cloud at the receiver. This can be done intentionally using a wide aperture receiver, or can be unintentional from other aspects of the receiver design. In a typical system, reflections from elsewhere in the scene or in an ambiguity zone for another point may cause performance degradation at the receiver. Other reflections can be avoided by assigning orthogonal sequences to known time intervals associated with ranging of specific points in the point cloud. This requires that the matched filter synchronously update its taps to reject other reflections. This embodiment is described in detail in the accompanying drawings. Figure 8 The rightmost sub-figure in FIG is shown, where the matched filter has been updated to reject sequences of neighboring points, thus rejecting P from outside the ambiguity range. 0 Reflected sequence X 0 .

[0073] Adaptively update sequence time attributes

[0074] Symbol rate adaptation

[0075] In some scenarios, different points may require different ranging resolutions. By identifying points in the point cloud that require higher ranging resolution, the adaptive transmitter can change the symbol rate of the sequence, which necessarily requires cooperative changes to the taps in the matched filter. In this case, there is a tradeoff with SNR, which can be partially or completely mitigated by increasing the averaging over equal length periods.

[0076] Get time adaptation

[0077] By adjusting the total acquisition time for each point, the point cloud can be redistributed to emphasize more important features. There are at least two possible advantages associated with this technique:

[0078] First, given fast feedback from the processing unit, the optical scanning system can be triggered to the output signal from the processor to remap each point acquisition time T i , to emphasize the more important features in the point cloud. The transmitter and matched filter can then be updated consistently to reflect the new acquisition time. For example, if orthogonal sequences are assigned to different points, the transmitted sequence will need to consist of a replicated sequence that matches the new acquisition time. When the acquisition time ends, the transmitter will then need to change to replicate a unique sequence for the next point. This is similar to Figure 8 The idea in is nothing more than an extension thereof, where each point (corresponding to a fixed time interval) is separated by a sequence of separate codes. In addition, here, for a specific point, the acquisition time of the specific point is adaptively changed. Fig. 9 shows that increasing P 0 An example of obtaining time to improve performance at that point.

[0079] Secondly, for scanning systems that need to wait to receive a transmitted pulse before moving to another point, such as with a narrow aperture system, the total flight time limits the total received sequence length that can be captured before moving to the next point. Alternatively, using a prior estimate of the distance of a point predicted or measured in a previous scan, additional sequences can be sent during the acquisition period to increase the SNR or ranging resolution point by point.

[0080] Orthogonal sequence length adaptation

[0081] The orthogonal sequence length can also be changed. This can be done to increase or decrease the ambiguity range. Alternatively, the orthogonal sequence length can be adjusted to target a specific point-by-point SNR. By reducing the orthogonal sequence length, and adaptively reducing the acquisition time (as described above), more points can be measured in a fixed measurement time.

[0082] Inserting timestamp

[0083] A timestamp can be added before, after, or within the quadrature pulses to differentiate them.

[0084] Fig.10 Describes the hardware diagram of the aforementioned embodiment. Note that according to various aspects described herein, Fig.10 Many other steps and sub-steps shown may be included in, or removed from, the flows shown above.

[0085] Correlation via a matched filter has been described in the foregoing embodiments. The linear filtering can be implemented in the time domain and / or the frequency domain. Non-linear processing [e.g., the method described in Van Trees] can be used. As an example of non-linear thresholding, a noise enhancement method can be used. Median filtering may be useful. Averaging is often useful. These methods can be combined.

[0086] For simplicity of implementation, a repeating pattern can be used. Much longer patterns can be used, in fact the pattern length can be much longer than the processing interval, for example 2 49 -1 pseudo-random sequence. To mitigate malicious detection or interference, an encrypted sequence can be used. AES-256 counter mode has 2 128 Using these long patterns, the receiver can be configured to correlate with a subset of the patterns that have been sent in the correlation time interval.

[0087] The mode may change in a predetermined manner or adaptively as described above.There may be a mode of modes.

[0088] Processing can occur in multiple processing units or processing algorithms. For example, pre-processing in one unit can reduce the amount of data sent to a second unit for further processing.

[0089] For simplicity of explanation, time domain adaptation has been described. The spectral content of the stimulus may have real-time adaptation. The statistical properties of the stimulus (eg peak-RMS, probability shaping or statistical moments) may be adapted in real-time.

[0090] It is often desirable to adapt the excitation and the corresponding receive processing to match. However, the adaptation may be full or partial excitation, pre-processing or processing.

[0091] The adaptation of the aforementioned embodiments may be a modulation or variation of the base pattern. For example, the base pattern may be an AES-256 counter pattern, and the adaptation is applied in the frequency domain to change the amplitude spectrum. In another example of adaptation, the base pattern may be time extended by changing the symbol interval. The interval may be ramped smoothly or may have discontinuous variations. Adaptation may be added to the base pattern. Adaptation may be an aspect of removing the base pattern.

[0092] Continuous wave (CW) light sources typically include smaller modulation or jitter in amplitude or phase or frequency than the subsequent modulation by the excitation pattern. CW light sources may also include intensity noise, phase noise, power supply noise, and other modulated or added components. CW light sources differ from pulsed sources in that considerable energy is present in the time interval covering multiple symbols.

[0093] The system can operate at multiple wavelengths in time series and / or in parallel. Multiple transmitters and / or receivers can operate with spatial or mode diversity. Aspects of processing different signals can occur in a common unit or algorithm or in different units. Self-adaptation can occur on different signals.

[0094] The self-adaptation may change the wavelength or the spatial or modal properties of the third optical signal.

[0095] The wavelength of the CW light source may advantageously be of the order of one micrometer. However, any wavelength less than one millimeter may be used when appropriate for the application.

[0096] Now go to Fig.11 , shows an illustrative embodiment of a communication device 1100. The communication device 1100 can be used in a fixed or mobile device. For example, the communication device 1100 can be used in a car such as an unmanned vehicle, a flying object such as an unmanned aerial vehicle (UAV), or can be used with a mobile device such as a Fig.10 It will be appreciated that the communication device 1100 may have Fig.10 For example, the communication device 1100 may not require the user interface 1104.

[0097] The communication device 1100 may include a wired and / or wireless transceiver 1102 (here, transceiver 1102), a user interface (UI) 1104, a power supply 1114, and a controller 1106 for managing its operation. The transceiver 1102 may support short-range or long-range wireless access technologies, such as Wi-Fi, DECT or cellular communication technologies, to name a few ( and They are respectively Special Interest Groups and Alliance). Cellular technologies may include, for example, CDMA-1X, UMTS / HSDPA, GSM / GPRS, TDMA / EDGE, EV / DO, WiMAX, SDR, LTE, and other emerging next generation wireless communication technologies. Transceiver 1102 may also be adapted to support circuit-switched wired access technologies (e.g., PSTN), packet-switched wired access technologies (e.g., TCP / IP, VoIP, etc.), and combinations thereof.

[0098] The UI 1104 may include a depressible or touch-sensitive keypad 1108 having a navigation mechanism, such as a scroll ball, joystick, mouse, or navigation pad for manipulating the operation of the communication device 1100. The keypad 1108 may be an integral part of the housing assembly of the communication device 1100, or may be connected to the communication device 1100 via a tethered wired interface (e.g., a USB cable) or ... a tethered wired interface (e.g., a USB cable) or a tethered wired interface (e.g., a USB cable The wireless interface of the communication device 1100 is operably coupled to a separate device. The keypad 1108 may represent a numeric keypad commonly used by phones and / or a QWERTY keypad with alphanumeric keys. The UI 1104 may also include a display 1110, such as a monochrome or color LCD (liquid crystal display), an OLED (organic light emitting diode), or other suitable display technology for transmitting images to an end user of the communication device 1100. In an embodiment where the display 1110 is touch-sensitive, part or all of the keypad 1108 may be presented by means of the display 1110 with navigation features.

[0099] The display 1110 may use touch screen technology so as to also serve as a user interface for detecting user input. As a touch screen display, the communication device 1100 may be adapted to present a user interface having graphical user interface (GUI) elements, which the user may select with the touch of a finger. The display 1110 may be equipped with capacitance, resistance, or other forms of sensing technology to detect how much surface area of ​​a user's finger has been placed on a portion of the touch screen display. This sensed information may be used to control manipulation of GUI elements or other functions of the user interface. The display 1110 may be an integral part of a housing assembly of the communication device 1100, or may be a separate device communicatively coupled thereto via a tethered wired interface (such as a cable) or a wireless interface.

[0100] The UI 1104 may also include an audio system 1112 that utilizes audio technology to transmit low volume audio (such as audio heard near a human ear) and high volume audio (such as a speaker phone for hands-free operation). The audio system 1112 may further include a microphone for receiving audible signals from an end user. The audio system 1112 may also be used for speech recognition applications. The UI 1104 may also include an image sensor 1113, such as a charge coupled device (CCD) camera, for capturing still or moving images.

[0101] The power source 1114 may utilize common power management techniques such as replaceable and rechargeable batteries, power conditioning techniques, and / or charging system techniques for providing energy to the components of the communication device 1100 to facilitate long-range or short-range portable communications. Alternatively or in combination, the charging system may utilize an external power source, such as DC power supplied via a physical interface such as a USB port or other suitable tethering technology.

[0102] The controller 1106 may utilize computing technology such as a microprocessor, a digital signal processor (DSP), a programmable gate array, an application specific integrated circuit, and / or a video processor with associated storage memory, such as flash memory, ROM, RAM, SRAM, DRAM, or other storage technology for executing computer instructions, controlling, and processing data provided by the above-mentioned components of the communication device 1100.

[0103] All subject matter in the appendix is ​​incorporated herein by reference, and any embodiments in the appendix may be combined in whole or in part with the subject disclosure.

[0104] Unless the context clearly indicates otherwise, the terms "first", "second", "third", etc. used herein are used only for clarification and do not otherwise indicate or imply any temporal order. For example, "first determination", "second determination", and "third determination" do not indicate or imply that the first determination is to be performed before the second determination, or vice versa, etc.

[0105] In addition, it will be noted that the disclosed subject matter can be practiced with other computer system configurations, including single-processor or multi-processor computer systems, small computing devices, mainframe computers, and personal computers, handheld computing devices (e.g., PDAs, phones, smart phones, watches, tablet computers, netbook computers, etc.), microprocessor-based or programmable consumer or industrial electronics, etc. The various aspects shown can also be practiced in a distributed computing environment, where tasks are performed by remote processing devices linked by a communication network; however, some aspects (if not all aspects) of the subject disclosure can be practiced on a stand-alone computer. In a distributed computing environment, program modules can be located in both local and remote memory storage devices. Some embodiments described herein can also use artificial intelligence (AI) to facilitate automating one or more features described herein. Classification as used herein also includes statistical regression for developing priority models.

[0106] As used in some contexts of the present application, in some embodiments, the terms "component", "system", etc. are intended to represent or include a computer-related entity or an entity related to an operating device having one or more specific functions, wherein the entity can be hardware, a combination of hardware and software, software, or software in execution. As an example, a component can be, but is not limited to, a process running on a processor, a processor, an object, an executable file, an execution thread, a computer executable instruction, a program, and / or a computer. As an illustration and not limitation, both applications running on a server and servers can be components. One or more components can reside in a process and / or a thread of execution, and a component can be located on a computer and / or distributed between two or more computers. In addition, these components can be executed from various computer-readable media having various data structures stored thereon. These components can communicate via local and / or remote processes, for example, according to a signal having one or more data packets (e.g., data from a component, which interacts with another component in a local system, a distributed system, and / or interacts with other systems via a network such as the Internet). As another example, a component may be a device having a specific functionality provided by mechanical parts operated by electrical or electronic circuits, which are operated by software or firmware applications executed by a processor, where the processor may be internal or external to the device and executes at least a portion of the software or firmware application. As yet another example, a component may be a device that provides a specific functionality through electronic components rather than mechanical parts, and the electronic components may include a processor to execute software or firmware that at least partially imparts the functionality to the electronic components. Although various components have been illustrated as separate components, it will be understood that multiple components may be implemented as a single component, or a single component may be implemented as multiple components, without departing from the example embodiments.

[0107] In addition, various embodiments may be implemented as a method, apparatus, or article of manufacture that uses standard programming and / or engineering techniques to produce software, firmware, hardware, or any combination thereof to control a computer to implement the disclosed subject matter. The term "article of manufacture" as used herein is intended to encompass a computer program accessible from any computer-readable device or computer-readable storage / communication medium.

[0108] In addition, the words "example" and "exemplary" are used herein to mean used as an example or illustration. Any embodiment or design described herein as an "example" or "exemplary" is not necessarily to be construed as being preferred or advantageous over other embodiments or designs. On the contrary, the use of the words example or exemplary is intended to present concepts in a concrete way. As used in this application, the term "or" is intended to mean an inclusive "or" rather than an exclusive "or". That is, unless otherwise specified or clear from the context, "X employs A or B" is intended to mean any natural inclusive arrangement. That is, if X uses A; X employs B; or X employs both A and B, then "X employs A or B" is satisfied under any of the foregoing examples. In addition, unless otherwise specified or clear from the context to refer to a singular form, the articles "one" and "an" used in this application and any appended claims should generally be interpreted as meaning "one or more".

[0109] As used herein, the term "processor" may refer to substantially any computational processing unit or device, including but not limited to a single-core processor; a single processor with software multithreaded execution capability; a multi-core processor; a multi-core processor with software multithreaded execution capability; a multi-core processor with hardware multithreading technology; a parallel platform; and a parallel platform with distributed shared memory. In addition, a processor may refer to an integrated circuit, an application-specific integrated circuit (ASIC), a digital signal processor (DSP), a field programmable gate array (FPGA), a programmable logic controller (PLC), a complex programmable logic device (CPLD), discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. The processor may employ a nanoscale architecture, such as, but not limited to, transistors, switches, and gates based on molecules and quantum dots, in order to optimize space usage or enhance the performance of user devices. The processor may also be implemented as a combination of computational processing units.

[0110] The above description only includes examples of various embodiments. Of course, it is not possible to describe every conceivable combination of components or methods for the purpose of describing these examples, but one of ordinary skill in the art will recognize that many further combinations and permutations of the given embodiments are possible. Therefore, the embodiments disclosed herein are intended to encompass all such changes, modifications and variations that fall within the spirit and scope of any appended claims. In addition, to the extent the term "comprising" is used in the detailed description or any claim, this term is intended to be inclusive in a manner similar to that in which the term "comprising" is interpreted when used as a transitional word in a claim.

[0111] Although specific embodiments have been illustrated and described herein, it should be understood that any arrangement to achieve the same or similar purpose may replace the embodiments described or shown by the subject disclosure. This subject disclosure is intended to cover any and all modifications or variations of various embodiments. The combination of the above-mentioned embodiments and other embodiments not specifically described herein may be used in the subject disclosure. For example, one or more features from one or more embodiments may be combined with one or more features of one or more other embodiments. In one or more embodiments, the features stated positively may also be stated negatively and excluded from the embodiments when replaced or not replaced by another structural and / or functional feature. The steps or functions described in the embodiments disclosed with respect to this subject may be performed in any order. The steps or functions described in the embodiments disclosed with respect to this subject may be performed alone or in combination with other steps or functions disclosed with respect to this subject, as well as performed from other embodiments or other steps never described in this subject disclosure. In addition, more or less than all the features described for the embodiments may also be utilized.

Claims

1. A device comprising: processing systems, including processors; as well as a memory storing executable instructions that, when executed by the processing system, facilitate performance of operations comprising: creating a first sequence of optical signals based on a first sequence of electrical signals provided to a continuous wave (CW) light source, the first sequence of electrical signals being associated with a plurality of matched filters; directing a first sequence of light signals toward a plurality of objects; receiving a second sequence of light signals based on reflections of the first sequence of light signals on the plurality of objects; converting the second optical signal sequence into a second electrical signal sequence; processing a second sequence of electrical signals according to the plurality of matched filters to extract information associated with the plurality of objects; adjusting the first electrical signal sequence to a third electrical signal sequence; adjusting the plurality of matched filters according to a third electrical signal sequence; applying a third sequence of electrical signals to the CW light source to generate an adjusted sequence of optical signals; and The modified sequence of light signals is directed to further improve the extracted information associated with the plurality of objects.

2. The device according to claim 1, wherein: Adjusting the first sequence of electrical signals to a third sequence of electrical signals is based on the extracted information, wherein adjusting the plurality of matched filters according to the third sequence of electrical signals is based on the extracted information, and wherein the adjusted sequence of optical signals is directed to the plurality of objects after the first sequence of optical signals is completed. 3 . The apparatus of claim 1 , wherein directing the adjustment sequence of the optical signal based on the extracted information occurs during a period of receiving the second optical signal sequence.

4. The apparatus of claim 3, wherein the time period is shorter than 100 microseconds or shorter than 10 times the round-trip time of light reflected from the plurality of objects, and wherein the length of the first electrical signal sequence is greater than the time period, wherein an information rate of the first electrical signal sequence or the second electrical signal sequence has a bit rate greater than 20 gigabits per second.

5. The device according to claim 1, wherein: The pattern length of the first electrical signal sequence is greater than 1000 symbols, wherein the symbol interval of the first electrical signal sequence is less than 50 picoseconds, wherein the processing of extracting the information is substantially linear or non-linear, and wherein the third electrical signal sequence and the first electrical signal sequence or the second electrical signal sequence are located in a single integrated circuit.

6. The device according to claim 1, wherein: The symbol sequence in the first electrical signal sequence or the second electrical signal sequence consists of a periodic sequence of symbols.

7. The device according to claim 1, wherein: The symbol sequences in the first electrical signal sequence and the third electrical signal sequence consist of different sequences of symbols, wherein the symbol sequences in the first electrical signal sequence and the third electrical signal sequence are substantially orthogonal, wherein the first optical signal sequence and the adjustment sequence of the optical signal are generated from the CW light source, and wherein the first electrical signal sequence and the third electrical signal sequence are generated by electro-optical modulation.

8. The device according to claim 1, wherein: The energy bandwidth associated with the first electrical signal sequence, the second electrical signal sequence, and the third electrical signal sequence is greater than 10 GHz, wherein the first electrical signal sequence, the second electrical signal sequence, and the third electrical signal sequence are composed of different subcarriers carrying dependent or independent sequences or subsequences, and the dependent or independent sequences or subsequences are subsequently processed by the multiple matched filters.

9. The device according to claim 1, wherein: The first electrical signal sequence, the second electrical signal sequence and the third electrical signal sequence are composed of different wavelengths carrying dependent or independent sequences or subsequences, which are then processed by the multiple matched filters, wherein the first optical signal sequence, the second optical signal sequence and the adjusted sequence of optical signals are transmitted through the air.

10. The device according to claim 1, wherein: Converting the second optical signal sequence into a second electrical signal sequence is performed by a detector having a bandwidth greater than 50 GHz, and wherein the detector is an intensity detector, wherein converting the second optical signal sequence into a second electrical signal sequence is performed using a coherent detector, wherein the coherent detector uses a portion of the CW light source as a local oscillator or uses another CW light source as a local oscillator.

11. The device according to claim 1, wherein: Processing the second electrical signal sequence includes performing analog-to-digital conversion and digital signal processing, wherein at least a portion of the digital signal processing is performed in an ASIC or FPGA, wherein the processing includes correlating the first electrical signal sequence and the second electrical signal sequence with a fixed-length matched filter.

12. The device according to claim 1, wherein: The extracted information includes absorption, delay, orientation, polarization or a combination thereof, wherein the extracted information is used to determine characteristics of the multiple objects, the characteristics including distance, speed, acceleration or a combination thereof, and wherein the symbol sequence associated with the third electrical signal sequence is generated based on at least a portion of the extracted information.

13. The apparatus according to claim 1, wherein: The third electrical signal sequence is composed of a symbol sequence having different electrical power relative to other sequences associated with the first electrical signal sequence, wherein the symbol sequence is orthogonal to the other symbol sequences associated with the first electrical signal sequence, wherein a first symbol rate of the first electrical signal sequence is different from a third symbol rate associated with the third electrical signal sequence, and wherein a total length of a first number of symbols of the first electrical signal sequence is different from a total length of a third number of symbols associated with the third electrical signal sequence.

14. An apparatus according to claim 1, wherein a first length of a first orthogonal sequence of a first electrical signal sequence is different from a third length of a third orthogonal sequence associated with a third electrical signal sequence, and wherein the taps in the multiple matched filters used for correlation are suitable for iteratively matching the first electrical signal sequence, the third electrical signal sequence, or a combination thereof.

15. A method comprising: creating a first sequence of optical signals based on a first sequence of electrical signals provided to a continuous wave (CW) light source, the first sequence of electrical signals being associated with a plurality of matched filters; directing a first sequence of light signals toward a plurality of objects; receiving a second sequence of light signals based on reflections of the first sequence of light signals on the plurality of objects; converting the second optical signal sequence into a second electrical signal sequence; processing a second sequence of electrical signals according to the plurality of matched filters to extract information associated with the plurality of objects; adjusting the first electrical signal sequence to a third electrical signal sequence; adjusting the plurality of matched filters according to a third electrical signal sequence; applying a third sequence of electrical signals to the CW light source to generate an adjusted sequence of optical signals; as well as The modified sequence of light signals is directed to further improve the extracted information associated with the plurality of objects.

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