Radar Hardware Accelerator

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First Claim
120. 20. (canceled)
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Abstract
A radar hardware accelerator (HWA) includes a fast Fourier transform (FFT) engine including a preprocessing block for providing interference mitigation and/or multiplying a radar data sample stream received from ADC buffers within a split accelerator local memory that also includes output buffers by a preprogrammed complex scalar or a specified sample from an internal lookup table (LUT) to generate preprocessed samples. A windowing plus FFT block (windowed FFT block) is for multiply the preprocessed samples by a window vector and then processing by an FFT block for performing a FFT to generate Fourier transformed samples. A postprocessing block is for computing a magnitude of the Fourier transformed samples and performing a data compression operation for generating postprocessed radar data. The preprocessing block, windowed FFT block and postprocessing block are connected in one streaming series data path.
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46 Claims
 120. 20. (canceled)
 21. A radar hardware accelerator (HWA), comprising:
a fast Fourier transform (FFT) engine including; a preprocessing block for generating preprocessed samples; a windowing plus FFT block (windowed FFT block) for multiplying the preprocessed samples by a window vector and then processing by an FFT block for performing a FFT to generate Fourier transformed samples; a postprocessing block for computing a magnitude of the Fourier transformed samples; and wherein the preprocessing block, the windowed FFT block, and the postprocessing block are connected in one streaming series data path.  View Dependent Claims (22, 23, 24, 25, 26, 27, 28, 29)
 30. A radar subsystem, comprising:
a split accelerator local memory including ADC input buffers (ADC buffers) for storing radar data sample streams, and output buffers; a radar hardware accelerator (HWA) coupled to the ADC buffers for receiving the radar data sample streams and for processing the radar data sample streams, the HWA including; a fast Fourier transform (FFT) engine including; a preprocessing block for generating preprocessed samples; a windowing plus FFT block (windowed FFT block) for multiplying the preprocessed samples by a window vector and then processing by an FFT block for performing a FFT to generate Fourier transformed samples; a postprocessing block for computing a magnitude of the Fourier transformed samples for generating postprocessed radar data, wherein the preprocessing block, the windowed FFT block, and the postprocessing block are connected in one streaming series data path, and wherein an output of the postprocessing block is coupled to an input of the output buffers for transferring the postprocessed radar data to the output buffers, and a parameterset configuration memory coupled to a state machine both coupled by a bus to the FFT engine for sequencing parameters sets for execution of a chained sequence of operations and data transfers between the accelerator local memory and an external memory for controlling the preprocessing block, the windowed FFT block and the postprocessing block.  View Dependent Claims (31, 32, 33, 34, 35, 36, 37, 38, 39)
 40. A method of (FMCW) radar signal processing using a radar hardware accelerator (HWA), comprising:
streaming postprocessed radar data to output buffers; transferring range fast Fourier transform (FFT) data from the output buffers to an external memory via direct memory accesses (DMA), the DMA being triggered automatically by the HWA; repeating the streaming and the transferring for radar data sample streams received by multiple antennas and across multiple chirps; wherein further processing is performed on the range FFT data originating from the multiple antennas and across the multiple chirps, comprising; transferring from the external memory in blocks to the output buffers, each the block including data for a first range gate and at least a second range gate; performing multiple doppler FFT'"'"'s using the HWA corresponding to the first range gate, wherein the doppler FFTs are computed for each of the multiple antennas in the first range gate; performing an absolute value operation on result of the doppler FFT'"'"'s for each of the multiple antennas corresponding to the first range gate, and summing results of the the absolute value operation across the multiple antennas, and repeating the further processing on subsequent data blocks from the data blocks corresponding to at least the second range gate.  View Dependent Claims (41, 42, 43, 44, 45, 46)
1 Specification
This application is a Continuation of application Ser. No. 15/184,715 filed Jun. 16, 2016,
Disclosed embodiments relate to hardware accelerators for radar systems.
Radar is used in many applications to detect target objects such as airplanes, military targets, vehicles, and pedestrians. Radar finds use in a number of applications associated with a motor vehicle such as for adaptive cruise control, collision warning, blind spot warning, lane change assist, parking assist and rear collision warning. Pulse radar or FrequencyModulated ContinuousWave (FMCW) radar are conventionally used in such applications.
In a radar system, a local oscillator (LO) generates a transmit signal. A voltage controlled oscillator (VCO) converts a voltage variation into a corresponding frequency variation. The transmit signal is amplified and transmitted by one or more transmit units. In FMCW radar, the frequency of the transmit signal is varied linearly with time. This transmit signal is referred as a ramp signal or a chirp signal. One or more obstacles scatters (or reflects) the transmit signal which is received by one or more receive units in the FMCW radar system.
A baseband signal is obtained from a mixer which mixes the transmitted LO signal and the received scattered signal that is termed an intermediate frequency (IF) signal. The IF signal is signal conditioned by a conditioning circuit which includes an amplifier and an antialias filter, is sampled by an analog to digital converter (ADC), and then is processed by a processor (e.g., microprocessor) to estimate a distance and a velocity of one or more nearby obstacles that provide scatter. Each peak in the fast Fourier transform (FFT) of the digitized IF signal corresponds to an object. The frequency of the IF signal is proportional to the range (distance) of the obstacle(s).
77 GHz automotive radar is a fastgrowing market segment, with a variety of existing and emerging applications. For example, the frequency of the transmitted chirp signal may be controlled to increase at a constant linear ramp rate from 77 GHz to 81 GHz in a period of about 100 microseconds. FMCW modulation is the preferred radar choice due to its various advantages including a large RF sweep bandwidth (enabling high range resolution), while keeping the IF/ADC bandwidth small, and lower peak power consumption needed as compared to pulsed radar.
The signal processing for FMCW radar systems (such as for advanced driver assist systems (ADAS)) is typically performed using a radar micro controller unit (MCU). The radar MCU generally includes a FFT hardware accelerator and a lockstep safety central processing unit (CPU) for object detection and tracking.
FMCW radar signal processing involves generating what is termed three (3) dimensions including the computation of a firstdimension (range) FFT, seconddimension (Doppler) FFT and thirddimension angleofarrival estimation processing (beamforming). An advantage of using a fast (sawtooth) FMCW radar waveform is that it can provide a two dimensional rangevelocity view of the objects illuminated by the radar, and additionally, the angleofarrival can be obtained through the use of multiple TX/RX antennas using digital beamforming.
This Summary briefly indicates the nature and substance of this Disclosure. It is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims.
Disclosed embodiments recognize known hardware accelerator (HWA) architectures for FMCW radar signal processing have several problems. Such problems include latency, lack of flexibility in sequencing data into and out of the HWA, and the radar signal processing that that is performed by the HWA is dependent on processor intervention.
Disclosed HWAs solve these problems with known HWA architecture for FMCW radar signal processing having several unique features which enables highperformance and flexibility for the customer, with support for offloading of some frequently used radar signal processing computations from the processor to the HWA. Disclosed HWAs include a fast Fourier transform (FFT) engine including a preprocessing block for providing at least one of interference mitigation, finite impulse response (FIR) filtering, and multiplying a radar data sample stream received from ADC buffers within a split accelerator local memory that also includes output buffers by a preprogrammed complex scalar or a specified sample from an internal lookup table (LUT) to generate preprocessed samples, a windowing plus FFT block (windowed FFT block) for multiplying the preprocessed samples by a window vector and then processing by a FFT block for performing a FFT to generate Fourier transformed samples, and a postprocessing block for computing a magnitude of the Fourier transformed samples and performing a data compression operation for generating postprocessed radar data. The processing block, windowed FFT block, and postprocessing block are connected in one streaming series data path which reduces latency.
Reference will now be made to the accompanying drawings, which are not necessarily drawn to scale, wherein:
Example embodiments are described with reference to the drawings, wherein like reference numerals are used to designate similar or equivalent elements. Illustrated ordering of acts or events should not be considered as limiting, as some acts or events may occur in different order and/or concurrently with other acts or events. Furthermore, some illustrated acts or events may not be required to implement a methodology in accordance with this disclosure.
Also, the terms “coupled to” or “couples with” (and the like) as used herein without further qualification are intended to describe either an indirect or direct electrical connection. Thus, if a first device “couples” to a second device, that connection can be through a direct electrical connection where there are only parasitics in the pathway, or through an indirect electrical connection via intervening items including other devices and connections. For indirect coupling, the intervening item generally does not modify the information of a signal but may adjust its current level, voltage level, and/or power level.
These FFT computations comprise obtaining the abovedescribed three (3) dimensions including the computation of a firstdimension (range) FFT, seconddimension (Doppler) FFT, and thirddimension angleofarrival estimation processing (beamforming). HWA 125 is shown in FIG, 1 and HWA 125′ in
Each of the preprocessing block 211, windowed FFT block 212 and postprocessing block 213 include an independent enable (EN) circuit shown in
The signal processing steps radar system portion 100 performs obtaining the threedimensional image of objects involves computing a firstdimension (range) FFT on the data samples from ADC buffers 120 corresponding to each transmitted chirp using the windowed FFT block 212. This is followed by a seconddimension (Doppler) FFT, which is performed across chirps, where the rangeFFT samples are fed in to the windowed FFT block 212 in transpose order compared to the firstdimension FFT. The angleofarrival estimation also involves FFT computations by windowed FFT block 212 with yet another transpose at the input. The HWA 125 also has a postprocessing block 213 for optionally computing a magnitude or logmagnitude of the radar image obtained from the FFT operations provided by the windowed FFT block 212. Further and optionally, the sum of the magnitude or logmagnitude of the radar image across a plurality of antennas can be obtained by passing the corresponding samples across antennas obtained at the output of the postprocessing block 213 through the FFT engine 210 and retaining only the first sample of the FFT engine output. This exploits the fact that the first output of an FFT computation represents the sum of the samples. Thus for computing the sum across 4 antennas, a 4point FFT would be computed for every 4 corresponding samples across antennas. Disclosed postprocessing is useful in preparing the FFT data for object detection. Object detection can be done by optionally employing a CFAR detection algorithm (see CFAR engine 220 in
The radar system portion 100 is typically on a single semiconductor (e.g., silicon) chip shown as a substrate 105 in
The radar system portion 100 includes an analog block 110 that represents the respective analog front end components (antenna(s), power amplifier, mixers, band pass filters, low noise amplifiers (LNA'"'"'s) and analogtodigital converters (ADCs)) that are coupled to a digital front end 115 that generally includes a decimator which downsamples and filters the samples output by the ADC before they are presented to an ADC input buffer pair (ADC buffers 120) which function to store the preprocessed radar data for the HWA 125. Although shown on chip, the antenna(s) may be off chip.
The ADC buffers 120 and the output buffers 130 together provide the local memories for the HWA 125 (together shown as accelerator local memories 217 in
The split aspect of the local memory 217 allows each of these 4 blocks of memory shown in
As shown in
An input formatter block 203 reads the input samples from the ADC buffers 120 and feeds them into the FFT engine 210 including the preprocessing block 211. The input formatter block 203 can be configured to perform a variety of tasks. For example, the input formatter block 203 can enable considerable flexibility in streaming data from the input memory (ADC buffers 120) into the HWA (using the 2D Memory indexing described below), can be configured to conjugate and/or scale the input data, can be configured to multiply the incoming data with a Binary Phase Modulation (BPM) pattern (which is a sequence of 1'"'"'s and −1'"'"'s), and can allow for circular indexing of the input memory which can be particularly useful if the HWA is being employed to do subband filtering using the FFTIFFT approach.
The preprocessing block 211 is for providing at least one of interference mitigation (e.g., zeroing out of radar samples whose magnitude exceeds a programmable limit), finite impulse response (FIR) filtering and performing a complex multiply operation on the radar data sample stream received from the input formatter 203. The complex multiply operation can be configured to be in one of various modes. In the frequency shift mode, the complex multiplier frequency derotates the radar data sample stream by a certain programmable frequency. In a scalar multiplication mode the radar data sample stream is multiplied by a preprogrammed complex scalar using the complex multiplier block 211c shown. In the vector multiplication mode the complex multiplier block 211c performs an element wise multiplication of the radar data sample stream and a complex vector that has been stored in the internal lookup table (LUT) 211a shown as a sin, cos LUT that is coupled to the complex multiplier block 211c. The preprocessing block 211 is also shown including an interference mitigation block 211d between the output of the input formatter 203 and the complex multiplier block 211c. The interference mitigation block 211d can use threshold comparison for zeroing out/clamping samples determined to be interference samples.
Preprocessing block 211 enables operations such as frequency shifting and FFT stitching. Regarding FFT stitching, the FFT Engine can perform streaming FFT'"'"'s of generally up to 1024 points. This capability suffices for most radar applications while still keeping the area of the HWA small. To perform FFT'"'"'s which are larger than 1024points, the HWA offers an “FFT Stitching capability” where multiple smaller size FFT'"'"'s computed on multiple subsets of a given input stream can be used to compute a larger size FFT of the entire input stream. As an example, when a 4K size FFT is needed, it is achieved in two steps. In the first step, every 4th input sample is passed through a 1K size FFT—i.e., four 1K point FFTs are performed on decimated input samples. Then, the resulting 4×1024 FFT outputs are sent through 4point “stitching” FFTs (1024 4point FFTs), which additionally involves a premultiplication by the complex multiplier block. The preprocessing block 211 also includes a FIR filter 211b for FIR filtering.
The windowed FFT block 212 is for multiplying the preprocessed samples by a window vector from windowcoefficients stored in the window RAM 212a and then processing by a FFT block 212b for performing a FFT to generate Fourier transformed samples. The postprocessing block 213 is for computing a magnitude of the Fourier transformed samples and performing a data compression operation (e.g., log2 operation) for generating postprocessed radar data. Data compression is optional and is configurable.
An output of the postprocessing block 213 is coupled by an output formatter block 216 to an input of the output buffers 130 for transferring the postprocessed radar data to the output buffers 130. The output formatter block 216 is responsible for writing the streaming processed output samples from postprocessing block 213 into the output buffers 130.
The output formatter block 216 can also be configured to perform a variety of tasks. For example, the output formatter block 216 can enable considerable flexibility in streaming data from the HWA into the output memory (using the 2DMemory indexing explained below), can be configured to conjugate and/or scale the data prior to storing in the output buffers 130 and ‘destination skip Sample’ feature which allows for certain number of output samples (from the HWA) to be skipped (i.e., discarded) in the beginning. This feature (in conjunction with the parameter DST_ACNT (to be explained below), allows only a specific contiguous subset of the output samples from the HWA to be stored in output memory. This can be useful, such as when only a specific subset of FFTbins are needed.
The HWA 125′ is shown including an optional CFAR engine 220 positioned in a CFAR detection path parallel to the streaming series data path, CFAR engine 220 includes a preprocessing block 221 and CFAR detector 222 for detecting radar target returns against background noise (e.g., clutter and interference). It is noted that since the FFT engine 210 and the CFAR engine 220 will generally not be operating simultaneously, and in order to reduce the area of the HWA, there can be sharing of memory and logic between these two engines.
A parameterset configuration memory 235 (e.g., implemented as RAM) is also shown coupled to a state machine 240 both coupled by a bus 145 to the FFT engine 210. As known in the art a state machine is any device that stores the status of something at a given time and can operate on input to change the status and/or cause an action or output to take place for any given change. The state machine 240 is responsible for controlling the operation of the HWA 125′ including for sequencing parametersets for execution of a chained sequence of computations and data transfers between the accelerator local memory 217 and an external memory 140, for controlling the preprocessing block 211, windowed FFT block 212 and postprocessing block 213. The state machine 240 can be configured to run through a sequence of parametersets starting and ending at specified indices (such as a start index and an end index). The state machine 240 can also be configured to loop through this sequence a specific number of times.
The parameterset configuration memory 235 is used to preconfigure the sets of parameters for a chained sequence of HWA operations. This memory can comprise an accelerator register configuration for the 16 different operations (each such configuration being referred to as a parameterset). This allows the HWA to perform preconfigured chained sequence of operations without frequent intervention from the μP 135′. Each parameterset includes various configuration details for each component inside the accelerator engine. For example, these configuration parameters can include the number of radar samples to read, starting memory address for sample read operation, memory base address, enable/disable for Core Computational engine operations (FFT, Magnitude, Phase, etc.), number of samples to write, starting memory address for sample write operation, etc. This feature enables meaningful chaining or sequencing of various radar signal processing operations with minimal intervention from the μP 135′ or other processor and as a result of that, makes efficient use of the capabilities of the FFT engine 210, triggering and DMA chaining options. The configuration registers 245 store common configuration information that is applicable to all parametersets.
The parameterset also allows for autonomous interfacing of the HWA with DMA'"'"'s for data transfer. Each parameterset can be configured to require the to trigger a DMA once it has completed the computations corresponding to the parameterset. This allows the HWA to initiate a transfer of data out of its output buffers 130, or to initiate transfer of a new set of input data into its input buffer provided by ADC buffers 120. The execution of each parameterset can also be made conditional on a trigger. This means that the state machine delays the execution of a scheduled parameterset, until the configured trigger condition is true. Examples of triggers include (1) An interrupt announcing the availability of data in the ADC buffer, (2) completion of a specific DMA transfer (3) software trigger from the main processor such as μp 135′.
The overall operation of the radar subsystem 200 can be summarized as follows. The FFT engine 210 is configured by the μP 135′ through the parameter configuration registers (or RAM) 245. Then, the state machine 240 kicks off and controls the overall operation of the HWA 125′, which involves loading the parameters needed for current operation from the parameterset configuration memory 235 into internal registers of the FFT engine 210 (or CFAR engine 220) and running the FFT engine 210 (or CFAR Engine 220) as per the programmed configuration. In one design, the FFT engine 210 and the associated memory (120, 130, 235, and 24) run on a 200 MHz clock.
Disclosed HWAs solve the abovedescribed problems with known HWAs by having the FFT engine 210 including Preprocessing, windowed FFT 212 and postprocessing blocks 213 in one streaming data path, along with a parameterset configuration memory 235 and state machine 240, such that a flexible sequence of operations (e.g., multidimensional FFT preprocessing, windowing FFT, and post processing 213, is performed backtoback without frequent intervention by the main processor 135 (μP 135′ in
Disclosed embodiments include a method of FMCW radar signal processing using a disclosed HWA. The method can comprise:
1. Streaming preprocessed radar data from an input buffer (e.g., ADC buffers 120) to an HWA 125 comprising a FFT engine 210 coupled to the ADC buffers for receiving and processing preprocessed radar data, where the HWA includes a FFT engine 210 that performs calculating including interferencethresholding, windowing FFT and range FFT to generate postprocessed radar data including range FFT data.
2. Streaming the postprocessed radar data to an output buffer 130.
3. Transferring the range FFT data from the output buffer 130 to an external memory (140) in a transpose fashion. The transferring can comprise direct memory access (DMA), with the DMA being triggered automatically by the HWA 125.
4. Repeating the calculating, streaming preprocessed and postprocessed radar data, and transferring the preprocessed streaming radar data received at multiple antennas (or more generically multiple channels). The range FFT data for multiple antennas across multiple chirps in a frame are computed and transferred as in 13 above.
The range FFT data originating from the multiple antennas across multiple chirps is then processed in further processing steps, comprising:
5. Transferring from the external memory 140 in blocks to an input memory (ADC buffers 120), with each block including data for one or more range gates across multiple chirps in a frame.
6. Performing multiple Doppler FFT'"'"'s using the HWA, each Doppler FFT corresponding to a specific antenna of each of the one or more range gates corresponding to a block. Additionally, the absolute values of the Doppler FFT bins are computed and these are summed across multiple antennas. The summing of the absolute value across multiple antennas can be performed by running an appropriate length FFT (for e.g. a 4 pointer for 4 antennas) in the HWA and then picking the first sample of the FFT output.
7. The Doppler FFTs computed in Step 6 and the sum of the absolute values of the Doppler FFT bins across antennas are both stored in external memory 140 via direct memory accesses (DMA), the DMA being triggered automatically by the HWA.
8. Repeating steps 5, 6, 7 across multiple blocks to cover all range gates corresponding to the rangeFFT.
The method can also further comprising detecting radar target returns against a back round using a CFAR engine 220 in a CFAR detection path parallel to the streaming series data path including a preprocessing block 221 and a CFAR detector 222. Samples corresponding to rangeFFT or Doppler FFT can be streamed through the CFAR detector 222 to detect peaks which are above a programmed specified threshold compared to the surrounding samples.
The CFAR engine 220, can also be employed for interference detection using a method described herein. The digitized time domain samples from the Digital front end (corresponding to a single chirp on a single channel) that are stored in the ADC buffers 120 are streamed into the CFAR Engine 220 of the HWA. The preprocessing block 221 of the CFAR Engine 220 can be used to compute the magnitude (or log magnitude) of the streamed samples. The output of the preprocessing block 221 is then streamed to the CFAR detector 222 which then detects samples whose magnitude is significantly above the average magnitude of the surrounding blocks (these samples are considered to be corrupted by interference). The indices of the detected samples are stored in the output buffer, Subsequently, the μp can read the list of indices of the detected samples and run any suitable algorithm (such as 1dimensional interpolation) for correcting the values of these samples.
A variant of the method described above is as follows. In this method the processing starts only when samples from the Digital front end corresponding to multiple chirps have been stored in the ADC buffers 120. The samples in the ADC buffers 120 can be viewed as being stored as a matrix, with each row corresponding to samples from the specific chirp. In the first step the samples from the ADC buffers 120 are sent rowwise into the CFAR engine to obtain a first series of lists, each list containing the indices of detected samples corresponding to each row.
In the second step, the samples from the ADC buffer 120 are sent column wise (using 2D Memory indexing) into the CFAR engine to obtain a second series of lists, each list containing the indices of detected samples corresponding to each column. In the third step the first series of lists and the second series of lists (that are stored in the output buffers 130 of the HWA) are examined by the μp (or other processor) to obtain a final list of samples from the ADC buffers 120 that are present in both the first list and the second list. This final list of samples is identified as being corrupted by interference. The μp can then employ any suitable algorithm to correct these corrupted samples (such as 2Dimensional interpolation).
Multiple dimensional computations, versatile access patterns from the input buffer into the HWA and to the output buffer from the HvvA are enabled by a new disclosed 2DMemory indexing scheme for memory access. Indexed memory addressing allows the significant flexibility in (a) the way in which data stored in the ADC buffers 120 is streamed into the HWA 125, and (b) the way in which data that is streamed out of the HWA 125 is stored in the output buffers 130. While each parameterset defines a specific configuration (or operation) of the HWA (and input formatter/output formatter), this specific configuration can operate on multiple radar data sample streams (or simply sample streams), the number of such sample streams, the number of input samples for each sample stream and input/output access pattern for each sample stream can also be programmed in the same parameterset. Thus for e.g., a single parameterset can be configured to perform a 256pt FFT on multiple sample streams (each sample stream, for e.g., corresponding to data from a different antenna).
In the 2DMemory indexing scheme, the streaming of data from the input memory (ADC buffers 120) to the HWA can be defined by the parameters: SRC_DR, SRC_ACNT, SRC_AIDX, BCNT, SRC_BIDX and SRC_ACNT. For streaming into the HWA 125 from ADC buffers 120 as input memory, a sample stream comprising SRC_ACNT samples (starting from SRC_ADDR) is streamed, each sample being SRC_AIDX bytes (which specifies the address offset (in bytes) separating successive samples) separated in the ADC buffers 120 as input memory from the previous, BCNT which specifies the number of iterations, such sample streams of SRC_ACNT samples each are streamed in, the first sample of each sample stream being separated by SRC_BINDX bytes from the preceding sample stream. Analogously, the streaming of data from the HWA to the output memory is defined by the parameters DST_ADDR, DST_ACNT, DST_AIDX, BCNT, DST_ BIDX. It is noted that the 2DMemory indexing scheme allows for different access patterns at the input and output. Thus, one has SRC_ADDR/DST_ADDR. SRC_AIDX/DST_AIDX etc. Only the number of iterations (BCNT) is generally consistent across both input and output streams.
In some embodiments the HWA might not include an FIR filter in the FFT block 210.In such embodiments filtering operations can be efficiently performed in the HWA as follows, In the first step the incoming samples are streamed into the HWA to perform an FFT (using a first parameterset). In the second step, the samples corresponding to the FFT are streamed into the HWA (using a second parameterset) with the preprocessing block 211 and the FFT engine 210both enabled. The complex multiplier is used to multiply the samples of the FFT with a complex vector that represents the frequency response of the desired filter and the FFT engine 222 performs an IFFT (inverse FFT) on the output of the preprocessing block. Thus the entire filtering operation is performed efficiently with just two streamings of the data through the HWA.
Those skilled in the art to which this disclosure relates will appreciate that many other embodiments and variations of embodiments are possible within the scope of the claimed invention, and further additions, deletions, substitutions and modifications may be made to the described embodiments without departing from the scope of this disclosure.