WO2022198566A1 - Speed estimation method and apparatus based on echo data - Google Patents

Abstract

The present application is applicable to the technical field of radars. Provided are a speed estimation method and apparatus based on echo data, which are used for autonomous driving or intelligent driving, and can complete speed estimation without relying on an inertial sensor. The method comprises: determining a local region in an imaging region; performing, in the local region, imaging processing on echo sub-data according to a plurality of first speeds to be processed, so as to obtain a plurality of first images to be processed, wherein the plurality of first speeds to be processed are obtained according to a preset speed range, the echo sub-data is obtained by means of dividing echo data, and each first image to be processed corresponds to one first speed to be processed; then, determining a target image to be processed from among the plurality of first images to be processed; and determining, as an estimated speed of the echo sub-data, the first speed to be processed that corresponds to the target image to be processed, and finally obtaining an estimated speed of the echo data. The present application can be applied to the Internet of Vehicles, such as vehicle-to-everything (V2X), long term evolution-vehicle (LTE-V) technology and vehicle-to-vehicle (V2V).

Description

A method and device for velocity estimation based on echo data technical field

The embodiments of the present application relate to the technical field of radar, and in particular, to a method and apparatus for estimating velocity based on echo data.

Background technique

Synthetic aperture radar (SAR) is an all-weather, all-weather modern remote sensing imaging radar with long-range and high-resolution detection capabilities. It is often used in remote sensing mapping, regional detection, geological exploration, disaster rescue and many other fields. . In the broader civil field, the vehicle-mounted SAR platform for intelligent driving is becoming a new round of research hotspots. Secondly, during the data acquisition process of SAR, the radar needs to move continuously to form a synthetic aperture, and the echo properties are closely related to the speed of the radar movement. In imaging processing, the relative motion velocity information of radar and target is one of the key parameters that need to be used in data processing of SAR imaging algorithm. Whether the recorded echoes can be accurately matched with the radar speed at that time will directly affect the imaging quality. However, when the vehicle is used as the working platform of the radar, it is difficult to maintain a stable speed for a long time in the road environment, which makes the vehicle SAR imaging more difficult. Therefore, obtaining the speed information of the radar in the process of picking up the echo has become an indispensable part of the work to obtain high-quality imaging results.

At present, SAR imaging systems mainly work on platforms such as aircraft or satellites. In such working platforms, high-precision inertial sensor systems are installed, which can provide accurate speed information for the imaging system.

However, in the vehicle platform, the application of such an inertial sensor system for imaging has a large hardware cost, and will increase the system complexity, and the inertial sensor system will have errors in the case of vibration, so there is an urgent need for an inertial sensor system. A velocity estimation method that does not rely on inertial sensors.

SUMMARY OF THE INVENTION

The embodiments of the present application provide a method and device for velocity estimation based on echo data, which can complete velocity estimation without relying on inertial sensors and reduce hardware costs.

A first aspect of the embodiments of the present application provides a velocity estimation method based on echo data. In the velocity estimation method, a local area is first determined from an imaging area, and a plurality of first to-be-processed velocities are obtained according to a preset velocity range , and divide the echo data to obtain multiple echo sub-data, perform imaging processing on one of the multiple echo sub-data in a local area according to the multiple first to-be-processed speeds, and obtain multiple first to-be-processed images , and each first to-be-processed image corresponds to a first to-be-processed speed, and based on this, the target to-be-processed image is determined from the plurality of first to-be-processed images. Since each first image to be processed corresponds to a first speed to be processed, the target image to be processed also corresponds to a first speed to be processed, so the first speed to be processed corresponding to the target image to be processed can be determined as the echo sub-data. The estimated velocity, the estimated velocity of the echo sub-data is used to obtain the estimated velocity of the echo data.

In this embodiment, the estimated velocity of the echo sub-data can be determined based on the echo data, and the estimated velocity of the echo data can be obtained through the estimated velocity of the echo sub-data, so the velocity estimation can be completed without relying on the inertial sensor, and the hardware is reduced. cost.

In combination with the first aspect of the embodiments of the present application, in the first implementation manner of the first aspect of the embodiments of the present application, the echo sub-data is imaged in a local area according to a plurality of first speeds to be processed, to obtain a plurality of Before the first image to be processed, the estimated speed range is divided at first preset speed intervals to obtain a plurality of first speeds to be processed. For example, if the preset speed range is 0 to 10 meters per second (m/s), based on this, the first preset speed interval may be determined to be 1 m/s, that is, 1 m/s to 0 to 10 m/s Divide, you can get 10 first pending speeds, then the 10 first pending speeds are 1m/s, 2m/s, 3m/s, 4m/s, 5m/s, 6m/s, 7m/s , 8m/s, 9m/s and 10m/s.

In this embodiment, by dividing the preset speed range by the first preset speed interval, the larger speed range can be reduced, so that the speed estimation can be performed more accurately in the smaller speed range, This improves the accuracy of velocity estimation.

With reference to the first implementation manner of the first aspect of the embodiments of the present application, in the second implementation manner of the first aspect of the embodiments of the present application, specifically for the multiple first to-be-processed directions of each first to-be-processed image The dimensions are superimposed along the same direction to obtain multiple first stacking direction dimensions of each first image to be processed, and then the first stacking direction dimension with the largest value among the multiple first stacking direction dimensions of each first image to be processed is calculated. is determined as the first quality evaluation index of each first image to be processed, and finally the first image to be processed with the largest value among the first quality evaluation indices of the plurality of first images to be processed is determined as the target image to be processed.

In this embodiment, since the first to-be-processed speed corresponding to the first to-be-processed image is closer to the real speed, the lines in the first to-be-processed image will be close to the vertical distance dimension, that is, in the direction dimension The lines are relatively clustered, so when the first speed to be processed is accurate, the values corresponding to the multiple direction dimensions are obtained after accumulating along each azimuth dimension, and then the maximum value among the values corresponding to the multiple direction dimensions is taken along the distance dimension, When it is inaccurate than the first to-be-processed speed, the maximum value obtained by a similar method is larger, so this value can be used as a quality evaluation index. Therefore, the first to-be-processed direction dimension in the first to-be-processed image with the largest value in the first quality evaluation index is relatively on a line similar to a straight line, so the determined first to-be-processed image corresponding to the target to-be-processed image at this time is determined The processing speed is closer to the real speed.

With reference to the second implementation manner of the first aspect of the embodiments of the present application, in the third implementation manner of the first aspect of the embodiments of the present application, the first quality evaluation index of the plurality of first images to be processed can also be included in the first quality evaluation index. The first image to be processed with the largest value is determined as the first estimated image, and a plurality of second speeds to be processed are obtained according to the first speed range, and then, in a similar manner to the first aspect of the embodiment of the present application, according to the plurality of second speeds to be processed. The second to-be-processed speed performs imaging processing on the first estimated image to obtain a plurality of second to-be-processed images, each second to-be-processed image corresponds to a second to-be-processed speed, and is determined from the plurality of second to-be-processed images The target image to be processed.

In this implementation manner, the first to-be-processed image with the largest value among the first quality evaluation indices of the plurality of first to-be-processed images is determined as the first estimated image (that is, the target to-be-processed image described above), At this time, the estimated velocity of the echo sub-data is not determined first, but the velocity estimation interval (ie, the first velocity range) is further narrowed. After imaging processing of each second velocity to be processed, the velocity estimation interval in a smaller area Determine the target image to be processed whose corresponding speed is more in line with the actual situation. This step can be repeated several times to improve the accuracy of the speed estimation.

With reference to the third implementation manner of the first aspect of the embodiments of the present application, in the fourth implementation manner of the first aspect of the embodiments of the present application, the first estimated image is imaged according to a plurality of second to-be-processed speeds. processing, before obtaining a plurality of second images to be processed, based on the first speed to be processed corresponding to the first estimated image, determine the first speed range, and divide the first speed range with the second first preset speed interval to obtain A plurality of second pending speeds. For example, if the first speed to be processed corresponding to the first estimated image is 3m/s, then the first speed range may be 2.5 to 3.5m/s. Based on this, the first speed range is divided by the second preset speed interval , to obtain a plurality of second speeds to be processed. For example, the second preset speed interval can be determined as 0.1m/s, that is, 0.1m/s is divided into 2.5 to 3.5m/s, and 11 first speeds can be obtained. Second pending speed, then 11 second pending speeds are 2.5m/s, 2.6m/s, 2.7m/s, 2.5m/s, 2.9m/s, 3.0m/s, 3.1m/s, 3.2m/s, 3.3m/s, 3.4m/s and 3.5m/s.

In this embodiment, by dividing the first speed range by the second preset speed interval, the speed range can be further reduced, so that the speed estimation can be performed more accurately in the smaller speed range, thereby improving the Accuracy of velocity estimates.

With reference to the fourth implementation manner of the first aspect of the embodiments of the present application, in the fifth implementation manner of the first aspect of the embodiments of the present application, the plurality of second to-be-processed direction dimensions of each second to-be-processed image are Superimpose along the same direction to obtain a plurality of second superposition direction dimensions of each second image to be processed, and determine the second superposition direction dimension with the largest value among the plurality of second superposition direction dimensions of each second image to be processed. For the second quality evaluation index of each second image to be processed, the second image to be processed with the largest value among the second quality evaluation indices of the plurality of second images to be processed is determined as the target image to be processed.

In this embodiment, since the second to-be-processed speed corresponding to the second to-be-processed image is closer to the real speed, the lines in the second to-be-processed image will be close to the vertical distance dimension. Therefore, when the second to-be-processed speed is accurate, the values corresponding to multiple direction dimensions are obtained after accumulating along each azimuth dimension, and then the maximum value among the values corresponding to multiple direction-dimensions is taken along the distance dimension, which will be faster than the second to-be-processed speed. When inaccurate, the maximum value obtained by similar methods is larger, so this value can be used as a quality evaluation index. Therefore, the first to-be-processed direction dimension in the second to-be-processed image with the largest value in the second quality evaluation index is relatively on a line similar to a straight line, so the determined second to-be-processed image corresponding to the target to-be-processed image at this time is determined. The processing speed is closer to the real speed.

In combination with any one of the first aspect of the embodiments of the present application to the fifth implementation manner of the first aspect of the embodiments of the present application, in the sixth implementation manner of the first aspect of the embodiments of the present application, it is also necessary to obtain the The echo data is divided by a preset step size to obtain a plurality of echo sub-data.

In this embodiment, by dividing the echo data, the above-mentioned multiple echo sub-data can be obtained, thereby ensuring that the velocity estimation method introduced in the above-mentioned embodiment can be performed on each echo sub-data, thereby improving the performance of this solution. feasibility.

With reference to the sixth implementation manner of the first aspect of the embodiments of the present application, in the seventh implementation manner of the first aspect of the embodiments of the present application, it is also necessary to perform filtering processing on the estimated velocities of multiple echo sub-data to obtain Estimated velocity of echo data.

In this embodiment, the speed estimation error is further reduced by the filtering process, thereby improving the speed estimation accuracy.

With reference to any one of the first aspect of the embodiments of the present application to the seventh implementation manner of the first aspect of the embodiments of the present application, in the eighth implementation manner of the first aspect of the embodiments of the present application, the direction of the imaging area is The dimension is larger than the direction dimension of the local area, and the distance dimension of the imaging area is larger than the distance dimension of the local area.

In this embodiment, the estimated velocity of the echo sub-data is determined by the local area in the imaging area, which can reduce the amount of calculation while improving the velocity estimation accuracy, thereby improving the velocity estimation efficiency.

A second aspect of the embodiments of the present application provides a speed estimation device, including:

a determination module for determining a local area from the imaging area;

a processing module, configured to perform imaging processing on the echo sub-data in a local area according to a plurality of first to-be-processed speeds to obtain a plurality of first to-be-processed images, wherein the plurality of first to-be-processed speeds are obtained according to a preset speed range , the echo sub-data is obtained by dividing the echo data, and each first image to be processed corresponds to a first speed to be processed;

a determining module, further configured to determine a target image to be processed from the plurality of first images to be processed;

The determining module is further configured to determine the first speed to be processed corresponding to the target image to be processed as the estimated speed of the echo sub-data, wherein the estimated speed of the echo sub-data is used to obtain the estimated speed of the echo data.

In an optional implementation manner of the present application, the speed estimation apparatus further includes a division module;

The division module is used to perform imaging processing on the echo sub-data in a local area according to the multiple first to-be-processed speeds to obtain multiple first to-be-processed images, and to perform an estimated speed range at the first preset speed interval. Divide to obtain a plurality of first speeds to be processed.

In an optional implementation manner of the present application, the determination module is specifically used for:

superimposing a plurality of first to-be-processed direction dimensions of each first to-be-processed image along the same direction to obtain a plurality of first superimposed direction dimensions of each first to-be-processed image;

Determine the first stacking direction dimension with the largest value among the multiple first stacking direction dimensions of each first image to be processed as the first quality evaluation index of each first image to be processed;

The first to-be-processed image with the largest value among the first quality evaluation indices of the plurality of first to-be-processed images is determined as the target to-be-processed image.

In an optional implementation manner of the present application, the determination module is specifically used for:

Determining the first image to be processed with the largest value among the first quality evaluation indices of the plurality of first images to be processed as the first estimated image;

Imaging processing is performed on the first estimated image according to a plurality of second to-be-processed speeds to obtain a plurality of second to-be-processed images, wherein the plurality of second to-be-processed speeds are obtained according to the first speed range, and each second to-be-processed speed The processed image corresponds to a second speed to be processed;

The target to-be-processed image is determined from the plurality of second to-be-processed images.

In an optional implementation manner of the present application, the determining module is further configured to, before the processing module performs imaging processing on the first estimated image according to the plurality of second to-be-processed speeds to obtain the plurality of second to-be-processed images, based on a first speed to be processed corresponding to the first estimated image, and a first speed range is determined;

The dividing module is further configured to divide the first speed range at second preset speed intervals to obtain a plurality of second speeds to be processed.

In an optional implementation manner of the present application, the determination module is specifically used for:

superimposing a plurality of second to-be-processed direction dimensions of each second to-be-processed image along the same direction to obtain a plurality of second superimposed direction dimensions of each second to-be-processed image;

Determining the second stacking direction dimension with the largest value among the multiple second stacking direction dimensions of each second image to be processed as the second quality evaluation index of each second image to be processed;

The second to-be-processed image with the largest value among the second quality evaluation indices of the plurality of second to-be-processed images is determined as the target to-be-processed image.

In an optional implementation manner of the present application, the speed estimation apparatus further includes an acquisition module;

an acquisition module for acquiring echo data;

The division module is further configured to divide the echo data with a preset step size to obtain a plurality of echo sub-data.

In an optional embodiment of the present application, the processing module is also used to filter the estimated speed of multiple echo sub-data to obtain the estimated speed of the echo data.

In an optional implementation manner of the present application, the direction dimension of the imaging area is larger than the direction dimension of the local area, and the distance dimension of the imaging area is larger than the distance dimension of the local area.

In a third aspect, a vehicle is provided, including a speed estimation device implementing any one of the possible implementations of the second aspect above.

In a fourth aspect, a processor is provided, including: an input circuit, an output circuit, and a processing circuit. The processing circuit is configured to receive a signal through the input circuit and transmit a signal through the output circuit, so that the processor executes the method in any one of the possible implementation manners of the first aspect.

In a specific implementation process, the above-mentioned processor may be a chip, the input circuit may be an input pin, the output circuit may be an output pin, and the processing circuit may be a transistor, a gate circuit, a flip-flop, and various logic circuits. The input signal received by the input circuit may be received and input by, for example, but not limited to, a receiver, the signal output by the output circuit may be, for example, but not limited to, output to and transmitted by a transmitter, and the input circuit and output The circuit can be the same circuit that acts as an input circuit and an output circuit at different times. The embodiments of the present application do not limit the specific implementation manners of the processor and various circuits.

In a fifth aspect, a speed estimation apparatus is provided, including a communication interface and a processor. The communication interface is coupled with the processor. The communication interface is used to input and/or output information. The information includes at least one of instructions and data. The processor is configured to execute a computer program to cause the speed estimation apparatus to perform the method of any possible implementation of the first aspect.

Optionally, there are one or more processors and one or more memories.

In a sixth aspect, a speed estimation apparatus is provided, including a processor and a memory. The processor is configured to read instructions stored in the memory, and can receive signals through a receiver and transmit signals through a transmitter, so that the apparatus performs the method in any possible implementation manner of the first aspect.

Optionally, there are one or more processors and one or more memories.

Optionally, the memory may be integrated with the processor, or the memory may be provided separately from the processor.

In the specific implementation process, the memory can be a non-transitory memory, such as a read only memory (ROM), which can be integrated with the processor on the same chip, or can be separately set in different On the chip, the embodiment of the present application does not limit the type of the memory and the setting manner of the memory and the processor.

It should be understood that the relevant information exchange process, for example, sending a message may be a process of outputting a message from the processor, and receiving a message may be a process of inputting a received message to the processor. Specifically, the information output by the processing can be output to the transmitter, and the input information received by the processor can be from the receiver. Among them, the transmitter and the receiver may be collectively referred to as a transceiver.

The speed estimation device in the fifth aspect and the sixth aspect may be a chip, and the processor may be implemented by hardware or software. When implemented by hardware, the processor may be a logic circuit, an integrated circuit, or the like; When implemented by software, the processor may be a general-purpose processor, which is implemented by reading software codes stored in a memory, which may be integrated in the processor or located outside the processor and exist independently.

In a seventh aspect, a computer program product is provided, the computer program product comprising: a computer program (also referred to as code, or instructions), which, when the computer program is executed, causes the computer to execute any one of the above-mentioned first aspects. A method in a possible implementation.

In an eighth aspect, a computer-readable storage medium is provided, the computer-readable storage medium stores a computer program (which may also be referred to as code, or an instruction), when it is run on a computer, causing the computer to execute the above-mentioned first aspect method in any of the possible implementations.

In a ninth aspect, the present application provides a chip system, the chip system includes a processor and an interface, the interface is used to obtain a program or an instruction, and the processor is used to call the program or instruction to implement or support the speed estimation device Implement the functions involved in the first aspect.

In a possible design, the chip system further includes a memory for storing necessary program instructions and data of the speed estimation device. The chip system may be composed of chips, or may include chips and other discrete devices.

It should be noted that, the beneficial effects brought by the embodiments of the second aspect to the ninth aspect of the present application can be understood with reference to the embodiments of the first aspect, and thus are not repeated.

Description of drawings

1 is a schematic diagram of an echo data collection scenario provided by an embodiment of the present application;

2 is a schematic flowchart of a method for estimating velocity based on echo data in an embodiment of the present application;

3 is a schematic diagram of an embodiment of determining a local area from an imaging area in an embodiment of the present application;

FIG. 4 is a schematic diagram of an embodiment of imaging in a local area in an embodiment of the present application;

FIG. 5 is a schematic flowchart of a backprojection imaging algorithm in an embodiment of the present application;

FIG. 6 is a schematic diagram of an embodiment of a plurality of first images to be processed in an embodiment of the present application;

FIG. 7 is a schematic diagram of another embodiment of a plurality of first images to be processed in an embodiment of the present application;

8 is a schematic flowchart of determining a target to-be-processed image from a plurality of first to-be-processed images in an embodiment of the present application;

FIG. 9 is a schematic diagram of an embodiment of a speed estimation result in an embodiment of the present application;

10 is another schematic flowchart of a method for estimating velocity based on echo data in an embodiment of the present application;

FIG. 11 is a schematic structural diagram of a speed estimation apparatus in an embodiment of the present application.

Detailed ways

In order to make the above objects, technical solutions and advantages of the present application easier to understand, a detailed description is provided below. The detailed description presents various embodiments of devices and/or processes through the use of block diagrams, flowcharts, and/or examples. Since these block diagrams, flowcharts and/or examples contain one or more functions and/or operations, those skilled in the art will understand that these block diagrams, Each function and/or operation within a flowchart or example. The terms "first", "second", "third", "fourth", etc. (if any) in the description and claims of this application and the drawings are used to distinguish similar objects and are not necessarily used to Describe a particular order or sequence. It is to be understood that data so used may be interchanged under appropriate circumstances so that the embodiments described herein can be practiced in sequences other than those illustrated or described herein. Furthermore, the terms "comprising" and "having" and any variations thereof, are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those expressly listed Rather, those steps or units may include other steps or units not expressly listed or inherent to these processes, methods, products or devices.

In order to better understand the echo data-based velocity estimation method and apparatus disclosed in the embodiments of the present application, the following first describes the system architecture used in the embodiments of the present invention. Please refer to FIG. 1. FIG. 1 is a schematic diagram of an echo data collection scenario provided by an embodiment of the present application. As shown in FIG. 1, the echo data is mainly collected by the synthetic aperture radar 120, and the synthetic aperture radar 120 is arranged on the top of the mobile carrier. , the synthetic aperture radar 120 may also be disposed in other parts of the mobile carrier, which is not specifically limited here. Secondly, the mobile carrier can be, for example, a collection vehicle 100, an unmanned aerial vehicle, a network device, etc. The above-mentioned vehicle 100 can be a car, a truck, a motorcycle, a bus, an amusement vehicle, an amusement park vehicle, a construction equipment, a tram and a train, etc. The application examples are not particularly limited.

Based on this, in the process of data acquisition, the synthetic aperture radar needs to perform continuous motion to form the synthetic aperture, and the echo properties are closely related to the speed of the radar movement. Therefore, in the imaging processing, the relative motion velocity information between the synthetic aperture radar and the target is one of the key parameters that need to be used in the data processing of the SAR imaging algorithm. Whether the recorded echoes can be accurately matched with the radar speed at that time will directly affect the imaging quality. However, when the vehicle is used as the working platform of the radar, it is difficult to maintain a stable speed for a long time in the road environment, which makes the vehicle SAR imaging more difficult. Therefore, obtaining the speed information of the radar in the process of picking up the echo has become an indispensable part of the work to obtain high-quality imaging results. At present, SAR imaging systems mainly work on platforms such as aircraft or satellites. In such platforms, high-precision inertial navigation systems are installed, which can provide accurate speed information for the imaging system. However, in the vehicle platform, the application of such an inertial navigation system for imaging has a large hardware cost, and will increase the system complexity, and the inertial sensor system will have errors in the case of vibration, so there is an urgent need for a kind of A velocity estimation method that does not rely on inertial sensors.

In order to solve the above problem, an embodiment of the present application provides a velocity estimation method based on echo data, which can complete velocity estimation without relying on inertial sensors and reduce hardware costs. The method for estimating velocity based on echo data provided by the embodiment of the present application will be described in detail below. Please refer to FIG. 2 , which is a schematic flowchart of the method for estimating velocity based on echo data in the embodiment of the present application, as shown in FIG. 2 . As shown, the specific steps of the velocity estimation method based on echo data are as follows.

S201, determining a local area from the imaging area.

In this embodiment, the speed estimation device needs to determine the local area from the imaging area. Specifically, the direction dimension of the imaging area is larger than the direction dimension of the local area, and the distance dimension of the imaging area is larger than the distance dimension of the local area. For example, the distance dimension of the imaging area is 0 to 20 meters, and the azimuth dimension is 0 to 20 meters. In this case, the distance dimension of the local area should be less than 20 meters, and the azimuth dimension should be less than 20 meters.

For ease of understanding, the distance dimension of the imaging area is 0 to 20 meters, and the azimuth dimension is 0 to 20 meters as an example for description. Please refer to FIG. 3 , which is the method of determining the local area from the imaging area in the embodiment of the application. A schematic diagram of the embodiment, as shown in FIG. 3 , the horizontal axis shown in FIG. 3 is the distance dimension, and the horizontal axis shown in FIG. 3 is the direction dimension. Based on this, the distance dimension of the imaging area 301 is 0 to 20 meters, and the azimuth dimension of the imaging area 301 is 0 to 20 meters. At this time, a local area 302 is determined from the imaging area 301, and the distance dimension of the local area 302 is 0 to 20 meters. 4 meters, and the azimuth dimension is 0 to 6 meters. Based on FIG. 3 , FIG. 4 is a schematic diagram of an embodiment of imaging in a local area in an embodiment of the present application. As shown in FIG. 4 , the distance dimension of the imaging result 401 obtained after imaging in the imaging area is 0 to 20 meters, And the azimuth dimension is 0 to 20 meters, and the distance dimension of the imaging result 402 obtained after imaging in the imaging area is 0 to 4 meters, and the azimuth dimension is 0 to 6 meters.

It should be understood that the foregoing examples are only used to understand this solution. In practical applications, the local area may also be located at other positions in the imaging area, and the specific distance dimension and specific direction dimension of the local area need to be tested through experiments and/or based on a large amount of data. The statistical determination of , therefore the foregoing examples should not be construed as limitations of this scheme.

S202: Perform imaging processing on the echo sub-data in a local area according to the multiple first to-be-processed speeds to obtain multiple first to-be-processed images.

In this embodiment, based on the scenario shown in FIG. 1 , after the velocity estimation device obtains the echo data through the synthetic aperture radar, the echo data is divided to obtain a plurality of echo sub-data. Based on this, this embodiment will first introduce how to perform velocity estimation on any echo sub-data in a plurality of echo sub-data.

First, the speed estimation device processes according to a preset speed range to obtain a plurality of first speeds to be processed. The preset speed range is determined by which mobile carrier the speed estimation device is set on. If the mobile carrier is a vehicle, the preset speed range is determined by the mobile carrier. The speed range is set to be the driving speed of the vehicle. Since the driving speed of each vehicle is different, the specific preset speed range also needs to be flexibly determined according to the actual situation. Specifically, the speed estimation device will divide the estimated speed range at the first preset speed interval to obtain a plurality of first speeds to be processed. For example, if the vehicle travels in a speed range of 0 to 36 kilometers per hour (km/h), the preset speed range may be determined to be 0 to 36 km/h, and 0 to 36 km/h is specifically 0 to 10 meters per hour Second (m/s), based on this, the first preset speed interval can be determined as 1m/s, that is, 1m/s is divided into 0 to 10m/s, and 10 first speeds to be processed can be obtained, Then the 10 first pending speeds are 1m/s, 2m/s, 3m/s, 4m/s, 5m/s, 6m/s, 7m/s, 8m/s, 9m/s and 10m/s, respectively.

Based on this, the speed estimation device performs imaging processing on the echo sub-data in the local area determined in step S201 according to the multiple first speeds to be processed, so as to obtain a first image to be processed corresponding to each of the first speeds to be processed. . Specifically, in this embodiment, the back projection (BP) imaging algorithm performs imaging processing on the echo sub-data in a local area, that is, in a dual-station synthetic aperture radar, the BP imaging algorithm reverses the echo sub-data by inverting the echo sub-data. To each pixel projected to the local area, the pixel value is imaged by calculating the time delay of the radar echo sub-data in the distance between the radar antenna and the image pixel, thereby obtaining the first image to be processed.

For easy understanding, please refer to FIG. 5 , which is a schematic flowchart of a backward projection imaging algorithm in an embodiment of the present application. As shown in FIG. 5 , in step S501 , the acquired echo sub-data is first input. Then, in step S502, the echo sub-data is subjected to demodulation (Dechirp) processing, and the range-dimensional pulse compression process is completed to obtain a high-resolution range image. Furthermore, in step S503, the sampling interval of the distance dimension and the sampling interval of the direction dimension are selected according to the resolution, and the sampling interval of the distance dimension and the azimuth dimension must be based on the resolution not greater than the respective dimensions. Based on the foregoing steps, in step S504, taking the distance line where each pixel is located as the center, take T _S /2 and T _S /2 to the left and right respectively, where T _s is the complete synthetic aperture time of the target location, That is, the time it takes for the target to be swept by a complete beam, taking the distance line where the pixel is located as the center, taking T _S /2 on the left and right, indicating that the scene position corresponding to this pixel is in the beam irradiation during this period of time. Then in step S5051, the time delay from the sampling point of each azimuth dimension to all pixel sampling points is calculated, and the corresponding range gate is determined, and in step S5052, the position of the synthetic aperture radar is calculated, and the corresponding direction dimension unit is determined . Based on the results of steps S5051 and S5052, in step S506, determine the compensation phase factor exp( _j4πRn /λ), where _Rn is the distance from the radar to each pixel at the current azimuth point. In step S507, based on the compensation phase factor exp( _j4πRn /λ), the signals on the cumulative curve are superimposed coherently, thereby generating a first image to be processed in step S508. It should be understood that in practical applications, imaging algorithms applied to SAR imaging such as Range Migration (RM) imaging algorithm, Range-Doppler (RD) imaging algorithm, etc., may also be used in local SAR imaging. The echo sub-data is imaged in the region, and all possibilities are not exhaustive and detailed here.

Therefore, based on the above algorithm, for each first speed to be processed, the echo sub-data can be imaged in a local area to obtain a first image to be processed corresponding to each first speed to be processed. For ease of understanding, please refer to FIG. 6 . FIG. 6 is a schematic diagram of an embodiment of a plurality of first images to be processed in an embodiment of the present application. As shown in FIG. 6 , (A) in FIG. A, the first to-be-processed image A obtained after performing imaging processing on the echo sub-data in the local area, similarly, (B) in FIG. 6 shows the echo sub-data in the local area according to the first to-be-processed speed B The first to-be-processed image B obtained after imaging processing, and (C) in FIG. 6 is the first to-be-processed image C obtained by imaging the echo sub-data in a local area according to the first to-be-processed speed C . It should be understood that the foregoing examples are only used for understanding this solution, and in practical applications, the specific first images to be processed corresponding to different first speeds to be processed are related to the imaging algorithm.

S203: Determine a target image to be processed from the plurality of first images to be processed.

In this embodiment, the speed estimation apparatus determines a target image to be processed among the plurality of first images to be processed obtained in step S202. Specifically, if the BP imaging algorithm is used to obtain multiple first images to be processed, if the first image to be processed corresponding to the first image to be processed is closer to the real speed, then the first image to be processed obtained after imaging processing will be Lines will appear. On the contrary, if the difference between the first to-be-processed speed corresponding to the first to-be-processed image and the real speed is greater, then deformed lines will appear in the first to-be-processed image obtained after imaging processing.

Further introduction is made based on FIG. 6 . FIG. 7 is a schematic diagram of another embodiment of a plurality of first images to be processed in the embodiment of the present application. As shown in FIG. 7 , a line 701 can be seen in (A) of FIG. 7 , the line 701 is deformed to the right of the direction dimension, so it can be determined that the first to-be-processed speed corresponding to the first to-be-processed image shown in (A) in FIG. 7 is smaller than the real speed. In (B) of FIG. 7 , a line 702 can be seen. At this time, the line 702 is basically perpendicular to the distance dimension. Therefore, the first image to be processed corresponding to the first image to be processed shown in (B) of FIG. 7 can be determined. The processing speed is close to the real speed. Next, the line 703 can be seen in (C) of FIG. 7 . At this time, the line 703 is deformed to the left of the direction dimension. Therefore, it can be determined that the first image to be processed shown in (C) in FIG. 7 corresponds to The first pending speed is greater than the true speed.

Specifically, since the first to-be-processed speed corresponding to the first to-be-processed image is closer to the real speed, the line in the first to-be-processed image will be close to the vertical distance dimension, that is, in the direction dimension, the line is Relatively aggregated, so when the first speed to be processed is accurate, the values corresponding to multiple direction dimensions are obtained after accumulating along each azimuth dimension, and then the maximum value among the values corresponding to multiple direction dimensions is taken along the distance dimension, which will be more When the processing speed is inaccurate, the maximum value obtained by a similar method is larger, so this value can be used as a quality evaluation index. Based on this, the speed estimating device can superimpose a plurality of first to-be-processed direction dimensions of each first to-be-processed image along the same direction to obtain a plurality of first superimposed direction dimensions of each first to-be-processed image, and then add each The first stacking direction dimension with the largest value among the multiple first stacking direction dimensions of the first images to be processed is determined as the first quality evaluation index of each first image to be processed, and then the The first image to be processed with the largest value in the first quality evaluation index is determined as the target image to be processed.

For ease of understanding, please refer to FIG. 8 . FIG. 8 is a schematic flowchart of determining a target to-be-processed image from a plurality of first to-be-processed images in an embodiment of the present application. As shown in FIG. The method can obtain N first to-be-processed speeds, where the N first to-be-processed speeds include the first to-be-processed speed A, the first to-be-processed speed B to the first to-be-processed speed N. Then, by the method described in step S202, imaging processing is performed on the first speed A to be processed, speed B to speed N to be processed in a local area, and the first speed corresponding to each speed to be processed can be obtained. Images to be processed, for example, the first image to be processed A corresponding to the first speed A to be processed, the first image B to be processed corresponding to the first speed B to be processed, to the first image to be processed corresponding to the first speed N to be processed N et al.

Further, each first to-be-processed direction dimension of each first to-be-processed image is superimposed along the same direction to obtain a plurality of first superimposed direction dimensions of each first to-be-processed image, for example, the first to-be-processed image A plurality of first stacking direction dimensions A are obtained for the image A, and a plurality of first stacking direction dimensions B are obtained for the first image B to be processed. Then, a first quality evaluation index is determined from a plurality of first stacking direction dimensions of each first image to be processed, and specifically, the first stacking direction dimension with the largest value among the plurality of first stacking direction dimensions is determined as the first quality assessment For the index, for example, the plurality of first stacking direction dimensions A include values of 3.0, 4.6, 6.4, 7.2 and 8.8, wherein the maximum value is 6.8, then the first quality evaluation index A is 6.8. Similarly, first quality assessment indices such as the first quality assessment index B and the first quality assessment index N can be obtained.

Based on this, the values of the first quality evaluation index A to the first quality evaluation index N are compared, and the target image to be processed is determined as the first image to be processed corresponding to the first quality evaluation index with the largest value. For example, the first quality assessment index A is 8.8, the first quality assessment index B is 9.8, the first quality assessment index C is 8.6, and the first quality assessment index N is 3.8. If it can be determined that the first quality assessment index B is N The maximum value among the first quality assessment indices, that is, the target to-be-processed image that can be determined by the first to-be-processed image B corresponding to the first quality assessment index B.

Specifically, the first image to be processed includes a plurality of pixel points, and each pixel point has a corresponding direction dimension and a distance dimension. Therefore, each first direction dimension to be processed of the first image to be processed is superimposed along the same direction, Actually, the direction dimensions of the pixels with the same distance dimension in the first image to be processed are superimposed, so as to obtain a plurality of first superimposed direction dimensions. For example, the first image to be processed includes pixel 1, pixel 2, pixel 3, pixel 4, pixel 5, and pixel 6, and the coordinates of pixel 1 are (3.8, 1.2), and the coordinates of pixel 2 are (2.8, 1.8), the coordinates of pixel 3 are (2.0, 2.0), the coordinates of pixel 4 are (1.6, 3.2), the coordinates of pixel 5 are (0.8, 3.8), and the coordinates of pixel 6 are (0.8 , 4.2). Among them, (3.8, 1.2) means that the distance dimension of pixel 1 is 3.8, and the direction dimension is 2. Similarly, it can be known that the distance dimension and direction dimension of other pixels are not all examples here. Based on this, it can be obtained that the distance dimension distribution of the pixels in the first image to be processed includes 3.8, 2.8, 2.0, 1.6 and 0.8, in which there is only one pixel in the distance dimension of 3.8, 2.8, 2.0 and 1.6, and the distance of 0.8 The dimension includes pixel point 5 and pixel point 6, so the direction dimension of the pixel point with the same distance dimension is superimposed, that is, the direction dimension of pixel point 5 and pixel point 6 needs to be superimposed, so that 5 first superimposed direction dimension can be achieved. , the values are 1.2, 1.8, 2.0, 3.2, and 8.0 (3.8+4.2=8.0) respectively, so it can also be determined that the first quality evaluation index of the first image to be processed is 8. It should be understood that the foregoing examples are all used to understand the present solution, but should not be construed as a limitation of the present solution.

S204: Determine the first to-be-processed speed corresponding to the target to-be-processed image as the estimated speed of the echo sub-data.

In this embodiment, since step S203 can determine the target image to be processed, and the first to-be-processed speed corresponding to the target to-be-processed image is the closest to the real speed among the multiple first to-be-processed speeds, the speed estimation device can The first to-be-processed speed corresponding to the to-be-processed image is determined as the estimated speed of the echo sub-data. This makes it possible to obtain the estimated velocity of echo data based on the estimated velocity of multiple echo sub-data subsequently.

Further, in this embodiment, based on the estimated velocity of the echo sub-data determined in the above step S204, the velocity estimation interval can be narrowed down, and the velocity estimation can be further performed, that is, the similar method shown in the step S202 to the step S204 is repeatedly performed, to Further improve the speed estimation accuracy.

Specifically, through the process shown in step S203, the speed estimation device determines the first to-be-processed image with the largest value among the first quality evaluation indices of the plurality of first to-be-processed images as the first estimated image (that is, the aforementioned step S203). The presented target image to be processed). At this time, the velocity estimation device does not perform the above step S204 to determine the estimated velocity of the echo sub-data, but determines the first velocity by a method similar to the above-mentioned step S202, that is, based on the first to-be-processed velocity corresponding to the first estimated image range, for example, if the first speed to be processed corresponding to the first estimated image is 3m/s, then the first speed range may be 2.5 to 3.5m/s. It should be understood that in practical applications, the first speed range may also be 2.4 to 3.4 m/s, or 2.6 to 3.6 m/s, the specific setting method of the first speed range is not limited here, and the first speed range only needs to include the first speed to be processed. Based on this, the first speed range is divided by the second preset speed interval to obtain a plurality of second speeds to be processed. For example, the second preset speed interval can be determined as 0.1m/s, that is, 0.1m/s s is divided into 2.5 to 3.5m/s, 11 second to-be-processed speeds can be obtained, then the 11 second-to-be-processed speeds are 2.5m/s, 2.6m/s, 2.7m/s, 2.5m/s respectively s, 2.9m/s, 3.0m/s, 3.1m/s, 3.2m/s, 3.3m/s, 3.4m/s and 3.5m/s.

Further, the speed estimating device superimposes a plurality of second to-be-processed direction dimensions of each second to-be-processed image along the same direction by a method similar to the above-mentioned step S203, to obtain a plurality of first-to-be-processed images of each second to-be-processed image. Two stacking direction dimensions, and the second stacking direction dimension with the largest value among the multiple second stacking direction dimensions of each second image to be processed is determined as the second quality evaluation index of each second image to be processed, and then The second to-be-processed image with the largest value among the second quality evaluation indices of the plurality of second to-be-processed images is determined as the target to-be-processed image. The specific manner is similar to that of step S203, and details are not repeated here.

At this time, the speed estimation apparatus has repeatedly performed the similar methods shown in steps S202 to S204 once. In order to improve the speed estimation accuracy, the similar methods shown in steps S202 to S204 can be performed again. In this embodiment, the accuracy and Power consumption during actual execution. The speed estimating device executes the similar method shown in steps S202 to S204 three times to determine the target image to be processed. In practical applications, the number of repetitions can be flexibly determined according to requirements, which is not limited at this time.

For ease of understanding, the speed estimation device is set in the vehicle, and the 77GHz millimeter wave radar is used as the signal transmitting and receiving device, and the speed estimation device performs the similar methods shown in steps S202 to S204 three times as an example. Please refer to FIG. 9 . FIG. 9 is a schematic diagram of an embodiment of the speed estimation result in the embodiment of the present application. As shown in FIG. 9 , (A) in FIG. 9 is the first execution of the method shown in step S202 to step S204 The obtained echo sub-data, an image obtained after performing imaging processing on the imaging region and the local region, includes an image 901 obtained after performing imaging processing on the imaging region and an image 902 obtained after performing imaging processing on the local region. Figure (B) in FIG. 9 is the echo sub-data obtained by performing the method shown in step S202 to step S204 for the second time, and the image obtained after performing imaging processing in the imaging area and the local area, including the image obtained after performing imaging processing in the imaging area The obtained image 903 and the image 904 obtained after the local area is subjected to imaging processing. Figure (C) in FIG. 9 is the echo sub-data obtained by performing the method shown in step S202 to step S204 for the third time, and the image obtained after imaging processing is performed on the imaging area and the local area, including the image obtained after performing imaging processing on the imaging area. The obtained image 905 and the image 906 obtained after the local area is subjected to imaging processing.

Based on this, it can be seen that, as shown in (A) of FIG. 9 , after the methods shown in steps S202 to S204 are performed for the first time, since the rough speed estimation is performed in a large speed range, the image The line 9021 included in 902 cannot be properly focused, and there is a large deformation. This deformation is more obvious in the image 901, and there is still a certain difference between the estimated speed determined at this time and the actual speed. Next, as shown in (B) of FIG. 9 , after performing the similar method from step S202 to step S204 for the second time, the deformation of the lines in the image 903 and the image 904 has been greatly improved, and the determined estimated The speed basically matches the real speed. Again, as shown in (C) of FIG. 9 , after performing the similar method of steps S202 to S204 for the second time, compared with the image shown in (B) of FIG. 9 , it is difficult to distinguish only with the naked eye , and the improvement in data is reflected in the image shown in (B) in Figure 9, the quality evaluation index obtained in the local area is 2.97E6, while in Figure 9 (C) shown in In the obtained image, the quality evaluation index obtained in the local area is 4.21E6. It can be seen that the speed estimation accuracy can be further improved by repeating the foregoing steps.

Therefore, in the method shown in the embodiment of FIG. 2 , the estimated velocity of the echo sub-data can be determined based on the echo data, and the estimated velocity of the echo data can be obtained by the estimated velocity of the echo sub-data, so it is possible to obtain the estimated velocity of the echo data. Speed estimation is done without relying on inertial sensors, reducing hardware costs. In addition, the local area in the imaging area determines the estimated velocity of the echo sub-data, which can reduce the amount of calculation while improving the velocity estimation accuracy, thereby improving the velocity estimation efficiency.

The embodiment of FIG. 2 mainly introduces the method for determining the estimated velocity of the echo sub-data. The following will introduce how to determine the estimated velocity of the echo data through the estimated velocity of the echo sub-data. Please refer to FIG. Another schematic flowchart of the velocity estimation method based on echo data in the embodiment of the application, as shown in FIG. 10 , the specific steps of the velocity estimation method based on echo data are as follows.

S1001, acquiring echo data.

In this embodiment, based on the scene shown in FIG. 1 , the velocity estimation apparatus can acquire echo data through synthetic aperture radar. The specific manner is similar to that described in step S202, and details are not repeated here.

S1002: Divide the echo data with a preset step size to obtain multiple echo sub-data.

In this embodiment, the velocity estimation apparatus divides the echo data with a preset step size to obtain a plurality of echo sub-data. Specifically, the preset step size means that the echo sub-data used in the current frame is advanced by a fixed length compared to the echo sub-data used in the previous frame, and multiple echo sub-data are the same. The meaning of multiple pieces of echo sub-data of the same size is that each frame of image contains the same number of sampling points. For example, assuming that each frame of image is obtained from 500 azimuth sampling point data, the preset step size is 100, and the previous frame The range of the echo sub-data used is 500 to 1000, and the range of the echo sub-data used in the current frame is 600-1100. In this way, the echo data is processed in a stepwise manner, and multiple echo sub-data can be obtained.

S1003 , filtering the estimated velocities of the multiple echo sub-data to obtain the estimated velocities of the echo data.

In this embodiment, the velocity estimation apparatus performs filtering processing on the estimated velocity of each echo sub-data, so as to further reduce the estimation error. Specifically, the method for filtering processing may include, but is not limited to, Kalman filter (Kalman filter, KF), Extended Kalman Filter (Extended Kalman Filter, EKF) and Sigma Point Kalman Filter (Sigma Point Kalman Filter, SPKF), etc., There is no specific limitation here.

The solutions provided by the embodiments of the present application have been introduced above mainly from the perspective of methods. It can be understood that, in order to realize the above-mentioned functions, the speed estimation apparatus includes corresponding hardware structures and/or software modules for executing each function. Those skilled in the art should easily realize that the present application can be implemented in hardware or in the form of a combination of hardware and computer software. Whether a function is performed by hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Skilled artisans may implement the described functionality using different methods for each particular application, but such implementations should not be considered beyond the scope of this application.

The embodiments of the present application may divide the speed estimation apparatus into functional modules based on the above method examples. For example, each functional module may be divided corresponding to each function, or two or more functions may be integrated into one processing module. The above-mentioned integrated modules can be implemented in the form of hardware, and can also be implemented in the form of software function modules. It should be noted that, the division of modules in the embodiments of the present application is schematic, and is only a logical function division, and there may be other division manners in actual implementation.

Therefore, the speed estimation device in the present application will be described in detail below. Please refer to FIG. 11 . FIG. 11 is a schematic structural diagram of the speed estimation device in the embodiment of the present application. As shown in the figure, the speed estimation device 1100 includes:

a determination module 1101, configured to determine a local area from the imaging area;

The processing module 1102 is configured to perform imaging processing on the echo sub-data in a local area according to a plurality of first to-be-processed speeds to obtain a plurality of first to-be-processed images, wherein the plurality of first to-be-processed speeds are obtained according to a preset speed range , the echo sub-data is obtained by dividing the echo data, and each first image to be processed corresponds to a first speed to be processed;

The determining module 1101 is further configured to determine the target image to be processed from the plurality of first images to be processed;

The determining module 1101 is further configured to determine the first speed to be processed corresponding to the target image to be processed as the estimated speed of the echo sub-data, wherein the estimated speed of the echo sub-data is used to obtain the estimated speed of the echo data.

In an optional implementation manner, on the basis of the embodiment corresponding to FIG. 11 above, in another embodiment of the speed estimation apparatus 1100 provided by this embodiment of the present application,

The speed estimation apparatus 1100 further includes a division module 1103;

The dividing module 1103 is used to perform imaging processing on the echo sub-data in the local area according to the multiple first to-be-processed speeds to obtain a plurality of first to-be-processed images, and use the first preset speed interval to estimate the speed range. Divide to obtain a plurality of first speeds to be processed.

In an optional implementation manner, on the basis of the embodiment corresponding to FIG. 11 above, in another embodiment of the speed estimation apparatus 1100 provided by this embodiment of the present application,

The determining module 1101 is specifically used for:

superimposing a plurality of first to-be-processed direction dimensions of each first to-be-processed image along the same direction to obtain a plurality of first superimposed direction dimensions of each first to-be-processed image;

Determine the first stacking direction dimension with the largest value among the multiple first stacking direction dimensions of each first image to be processed as the first quality evaluation index of each first image to be processed;

The first to-be-processed image with the largest value among the first quality evaluation indices of the plurality of first to-be-processed images is determined as the target to-be-processed image.

In an optional implementation manner, on the basis of the embodiment corresponding to FIG. 11 above, in another embodiment of the speed estimation apparatus 1100 provided by this embodiment of the present application,

The determining module 1101 is specifically used for:

Determining the first image to be processed with the largest value among the first quality evaluation indices of the plurality of first images to be processed as the first estimated image;

Imaging processing is performed on the first estimated image according to a plurality of second to-be-processed speeds to obtain a plurality of second to-be-processed images, wherein the plurality of second to-be-processed speeds are obtained according to the first speed range, and each second to-be-processed speed The processed image corresponds to a second speed to be processed;

The target to-be-processed image is determined from the plurality of second to-be-processed images.

In an optional implementation manner, on the basis of the embodiment corresponding to FIG. 11 above, in another embodiment of the speed estimation apparatus 1100 provided by this embodiment of the present application,

The determination module 1101 is further configured to perform imaging processing on the first estimated image according to multiple second to-be-processed speeds to obtain multiple second to-be-processed images, based on the first to-be-processed image corresponding to the first estimated image Speed, determine the first speed range;

The dividing module 1103 is further configured to divide the first speed range at second preset speed intervals to obtain a plurality of second speeds to be processed.

In an optional implementation manner, on the basis of the embodiment corresponding to FIG. 11 above, in another embodiment of the speed estimation apparatus 1100 provided in this embodiment of the present application,

The determining module 1101 is specifically used for:

superimposing a plurality of second to-be-processed direction dimensions of each second to-be-processed image along the same direction to obtain a plurality of second superimposed direction dimensions of each second to-be-processed image;

Determining the second stacking direction dimension with the largest value among the multiple second stacking direction dimensions of each second image to be processed as the second quality evaluation index of each second image to be processed;

The second to-be-processed image with the largest value among the second quality evaluation indices of the plurality of second to-be-processed images is determined as the target to-be-processed image.

In an optional implementation manner, on the basis of the embodiment corresponding to FIG. 11 above, in another embodiment of the speed estimation apparatus 1100 provided by this embodiment of the present application,

The speed estimation apparatus 1100 further includes an obtaining module 1104;

an acquisition module 1104, configured to acquire echo data;

The dividing module 1103 is further configured to divide the echo data with a preset step size to obtain a plurality of echo sub-data.

In an optional implementation manner, on the basis of the embodiment corresponding to FIG. 11 above, in another embodiment of the speed estimation apparatus 1100 provided by this embodiment of the present application,

The processing module 1102 is further configured to filter the estimated velocities of the multiple echo sub-data to obtain the estimated velocities of the echo data.

In an optional implementation manner, on the basis of the embodiment corresponding to FIG. 11 above, in another embodiment of the velocity estimation apparatus 1100 provided in this embodiment of the present application, the direction dimension of the imaging area is greater than the direction dimension of the local area. , the distance dimension of the imaging area is larger than that of the local area.

The present application also provides a speed estimation apparatus, including at least one processor, where the at least one processor is configured to execute a computer program stored in a memory, so that the speed estimation apparatus executes the speed estimation apparatus in any of the above method embodiments method performed.

It should be understood that the above-mentioned speed estimation device may be one or more chips. For example, the speed estimation device may be a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a system on chip (SoC), or a system on chip (SoC). It can be a central processing unit (CPU), a network processor (NP), a digital signal processing circuit (DSP), or a microcontroller (microcontroller). unit, MCU), it can also be a programmable logic device (PLD) or other integrated chips.

The embodiments of the present application also provide a speed estimation apparatus, which includes a processor and a communication interface. The communication interface is coupled with the processor. The communication interface is used to input and/or output information. The information includes at least one of instructions and data. The processor is configured to execute a computer program, so that the speed estimation apparatus executes the method performed by the speed estimation apparatus in any of the above method embodiments.

The embodiments of the present application also provide a speed estimation apparatus, which includes a processor and a memory. The memory is used to store a computer program, and the processor is used to call and run the computer program from the memory, so that the speed estimation apparatus executes the method performed by the speed estimation apparatus in any of the above method embodiments.

In the implementation process, each step of the above-mentioned method can be completed by a hardware integrated logic circuit in a processor or an instruction in the form of software. The steps of the methods disclosed in conjunction with the embodiments of the present application may be directly embodied as executed by a hardware processor, or executed by a combination of hardware and software modules in the processor. The software modules may be located in random access memory, flash memory, read-only memory, programmable read-only memory or electrically erasable programmable memory, registers and other storage media mature in the art. The storage medium is located in the memory, and the processor reads the information in the memory, and completes the steps of the above method in combination with its hardware. To avoid repetition, detailed description is omitted here.

According to the method provided by the embodiment of the present application, the present application further provides a vehicle, the vehicle including executing the speed estimation device in the embodiment shown in FIG. 2 , FIG. 5 , FIG. 8 and FIG. 10 .

According to the method provided by the embodiment of the present application, the present application also provides a computer program product, the computer program product includes: computer program code, when the computer program code is run on a computer, the computer is made to execute FIG. 2 , FIG. 5 , Methods performed by various units in the embodiments shown in FIG. 8 and FIG. 10 .

According to the method provided by the embodiment of the present application, the present application also provides a computer-readable storage medium, where the computer-readable storage medium stores program codes, and when the program codes are run on a computer, the computer is made to execute FIG. 2 , and FIG. 5, and the method performed by each unit in the embodiment shown in FIG. 10 and FIG. 8 .

The modules in the above-mentioned device embodiments correspond to the units in the method embodiments completely, and the corresponding modules or units perform corresponding steps. Other steps may be performed by a processing unit (processor). For functions of specific units, reference may be made to corresponding method embodiments. The number of processors may be one or more.

In the several embodiments provided in this application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the apparatus embodiments described above are only illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components may be combined or Can be integrated into another system, or some features can be ignored, or not implemented. On the other hand, the shown or discussed mutual coupling or direct coupling or communication connection may be through some interfaces, indirect coupling or communication connection of devices or units, and may be in electrical, mechanical or other forms.

The units described as separate components may or may not be physically separated, and components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution in this embodiment.

In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically alone, or two or more units may be integrated into one unit.

The functions, if implemented in the form of software functional units and sold or used as independent products, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be embodied in the form of a software product in essence, or the part that contributes to the prior art or the part of the technical solution. The computer software product is stored in a storage medium, including Several instructions are used to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), magnetic disk or optical disk and other media that can store program codes .

The above are only specific embodiments of the present application, but the protection scope of the present application is not limited to this. should be covered within the scope of protection of this application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims (21)

1. A velocity estimation method based on echo data, characterized in that the method comprises:

   determine the local area from the imaging area;

   Perform imaging processing on the echo sub-data in the local area according to a plurality of first to-be-processed speeds to obtain a plurality of first to-be-processed images, wherein the plurality of first to-be-processed speeds are obtained according to a preset speed range, The echo sub-data is obtained by dividing the echo data, and each first image to be processed corresponds to a first speed to be processed;

   determining a target image to be processed from the plurality of first images to be processed;

   The first speed to be processed corresponding to the target image to be processed is determined as the estimated speed of the echo sub-data, wherein the estimated speed of the echo sub-data is used to obtain the estimated speed of the echo data.
2. The method according to claim 1, characterized in that, before the echo sub-data is subjected to imaging processing in the local area according to a plurality of first speeds to be processed to obtain a plurality of first images to be processed, the method Also includes:

   The estimated speed range is divided at first preset speed intervals to obtain the plurality of first speeds to be processed.
3. The method according to claim 2, wherein the determining the target image to be processed from the plurality of first images to be processed comprises:

   superimposing a plurality of first to-be-processed direction dimensions of each first to-be-processed image along the same direction to obtain a plurality of first superimposed direction dimensions of each first to-be-processed image;

   Determine the first stacking direction dimension with the largest value among the multiple first stacking direction dimensions of each first image to be processed as the first quality evaluation index of each first image to be processed;

   The first to-be-processed image with the largest value among the first quality evaluation indices of the plurality of first to-be-processed images is determined as the target to-be-processed image.
4. The method according to claim 3, wherein determining the first image to be processed with the largest value among the first quality evaluation indices of the plurality of first images to be processed as the target image to be processed comprises:

   determining the first image to be processed with the largest value among the first quality evaluation indices of the plurality of first images to be processed as the first estimated image;

   Perform imaging processing on the first estimated image according to a plurality of second to-be-processed speeds to obtain a plurality of second to-be-processed images, wherein the plurality of second to-be-processed speeds are obtained according to the first speed range , each second to-be-processed image corresponds to a second to-be-processed speed;

   The target image to be processed is determined from the plurality of second images to be processed.
5. The method according to claim 4, wherein before the imaging processing is performed on the first estimated image according to the plurality of second to-be-processed speeds to obtain a plurality of second to-be-processed images, the method further comprises: include:

   determining a first speed range based on the first speed to be processed corresponding to the first estimated image;

   The first speed range is divided at second preset speed intervals to obtain a plurality of second speeds to be processed.
6. The method according to claim 5, wherein the determining the target image to be processed from the plurality of second images to be processed comprises:

   superimposing a plurality of second to-be-processed direction dimensions of each second to-be-processed image along the same direction to obtain a plurality of second superimposed direction dimensions of each second to-be-processed image;

   Determining the second stacking direction dimension with the largest value among the multiple second stacking direction dimensions of each second image to be processed as the second quality evaluation index of each second image to be processed;

   The second to-be-processed image with the largest value among the second quality evaluation indices of the plurality of second to-be-processed images is determined as the target to-be-processed image.
7. The method according to any one of claims 1 to 6, wherein the method further comprises:

   obtaining the echo data;

   The echo data is divided by a preset step size to obtain a plurality of the echo sub-data.
8. The method according to claim 7, wherein the method further comprises:

   Filtering is performed on the estimated velocities of the multiple echo sub-data to obtain the estimated velocities of the echo data.
9. The method according to any one of claims 1 to 8, wherein the direction dimension of the imaging area is larger than the direction dimension of the local area, and the distance dimension of the imaging area is larger than the distance dimension of the local area .
10. A speed estimation device, characterized in that the speed estimation device comprises:

    a determination module for determining a local area from the imaging area;

    a processing module, configured to perform imaging processing on the echo sub-data in the local area according to a plurality of first to-be-processed velocities to obtain a plurality of first to-be-processed images, wherein the plurality of first to-be-processed velocities are based on preset The echo sub-data is obtained by dividing the echo data, and each first to-be-processed image corresponds to a first to-be-processed speed;

    The determining module is further configured to determine a target image to be processed from the plurality of first images to be processed;

    The determining module is further configured to determine the first speed to be processed corresponding to the target image to be processed as the estimated speed of the echo sub-data, wherein the estimated speed of the echo sub-data is used to obtain the Estimated velocity of echo data.
11. The speed estimation device according to claim 10, wherein the speed estimation device further comprises a dividing module;

    The dividing module is configured to, before the processing module performs imaging processing on the echo sub-data in the local area according to a plurality of first to-be-processed speeds to obtain a plurality of first to-be-processed images, at a first preset speed interval The estimated speed range is divided to obtain the plurality of first speeds to be processed.
12. The speed estimation device according to claim 11, wherein the determining module is specifically configured to:

    superimposing a plurality of first to-be-processed direction dimensions of each first to-be-processed image along the same direction to obtain a plurality of first superimposed direction dimensions of each first to-be-processed image;

    Determine the first stacking direction dimension with the largest value among the multiple first stacking direction dimensions of each first image to be processed as the first quality evaluation index of each first image to be processed;

    The first to-be-processed image with the largest value among the first quality evaluation indices of the plurality of first to-be-processed images is determined as the target to-be-processed image.
13. The speed estimation device according to claim 12, wherein the determining module is specifically configured to:

    determining the first image to be processed with the largest value among the first quality evaluation indices of the plurality of first images to be processed as the first estimated image;

    Perform imaging processing on the first estimated image according to a plurality of second to-be-processed speeds to obtain a plurality of second to-be-processed images, wherein the plurality of second to-be-processed speeds are obtained according to the first speed range , each second to-be-processed image corresponds to a second to-be-processed speed;

    The target image to be processed is determined from the plurality of second images to be processed.
14. The speed estimation device according to claim 13, wherein the determining module is further configured to perform imaging processing on the first estimated image according to a plurality of second speeds to be processed in the processing module, to obtain a plurality of second speeds to be processed. Before the second image to be processed, determine a first speed range based on the first speed to be processed corresponding to the first estimated image;

    The dividing module is further configured to divide the first speed range at second preset speed intervals to obtain a plurality of second speeds to be processed.
15. The speed estimation device according to claim 14, wherein the determining module is specifically configured to:

    superimposing a plurality of second to-be-processed direction dimensions of each second to-be-processed image along the same direction to obtain a plurality of second superimposed direction dimensions of each second to-be-processed image;

    Determining the second stacking direction dimension with the largest value among the multiple second stacking direction dimensions of each second image to be processed as the second quality evaluation index of each second image to be processed;

    The second to-be-processed image with the largest value among the second quality evaluation indices of the plurality of second to-be-processed images is determined as the target to-be-processed image.
16. The speed estimation device according to any one of claims 10 to 15, wherein the speed estimation device further comprises an acquisition module;

    the acquisition module, configured to acquire the echo data;

    The dividing module is further configured to divide the echo data with a preset step size to obtain a plurality of the echo sub-data.
17. The speed estimation apparatus according to claim 16, wherein the processing module is further configured to filter the estimated speeds of the multiple echo sub-data to obtain the estimated speeds of the echo data.
18. The speed estimation device according to any one of claims 10 to 17, wherein the direction dimension of the imaging area is larger than the direction dimension of the local area, and the distance dimension of the imaging area is larger than the local area dimension. distance dimension.
19. A vehicle, characterized by comprising the speed estimating device according to any one of claims 10 to 18.
20. A chip, characterized in that the chip includes at least one processor, the at least one processor is connected in communication with at least one memory, and the at least one memory stores instructions; the instructions are processed by the at least one processor The method of any one of claims 1 to 9 is performed.
21. A computer-readable storage medium having stored therein instructions which, when executed on a computer, cause the computer to perform the method of any one of claims 1 to 9.

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