CN112578351A - Target matching method, integrated circuit, radio device and apparatus - Google Patents
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Abstract
The application discloses a target matching method, an integrated circuit, a radio device and equipment. The target matching method comprises the following steps: obtaining a plurality of first target data and a plurality of second target data; selecting at most K second target data to construct a first candidate matching queue of each first target data, wherein a first matching object of the queue is a candidate matching object with the minimum difference degree with the first target data; selecting at most K first target data to construct a second candidate matching queue of each second target data, wherein a first matching object of the queue is a candidate matching object with the minimum difference degree with the second target data; and determining the first target data and the second target data which are first matching objects to be target data pairs which are adapted to the same target until each first target data is matched or the first candidate matching queue thereof is empty. The target matching method can reduce power consumption of the radio device and increase operation speed.
Description
The present application claims priority from chinese patent application filed on 28.02/2020, having application number 202010131649.2 entitled "target matching method and radar system", which is incorporated herein by reference in its entirety.
Technical Field
The present invention relates to the field of radar technology, and more particularly, to a target matching method, an integrated circuit, a radio device, and a device.
Background
At present, in order to realize functions of target detection and tracking, in operation processes of obtaining a track of a target, eliminating speed ambiguity and the like, target matching operation is generally performed by utilizing matrix operation and the like, so that the calculation complexity is higher, and meanwhile, when the number of targets is increased, the time complexity is further improved, and further the running time is obviously increased.
Therefore, it is desirable to provide a new target matching method to reduce the computational complexity and time complexity, thereby reducing the power consumption of the device and increasing the operation speed of the device.
Disclosure of Invention
In view of the above problems, it is an object of the present invention to provide a target matching method, an integrated circuit, a radio device, and an apparatus, which reduce the amount of computation and time complexity, thereby reducing the power consumption of the radio device and increasing the operation speed.
In one aspect, the present disclosure provides a target matching method, which can be applied to target matching between two unit signals, including but not limited to target matching between two frame signals, where the definition of a specific unit signal can be adaptively adjusted according to actual requirements, and the method can include:
obtaining a first data set and a second data set, wherein the first data set can comprise a plurality of first target data, and the second data set can comprise a plurality of second target data;
for each first target data in a first data set, selecting at most K second target data in a second data set as candidate matching objects of the first target data to construct a first candidate matching queue for each first target data, wherein the first matching object of the first target data is the candidate matching object with the smallest difference degree with the first target data in the first candidate matching queue;
for each second target data in a second data set, selecting at most K first target data in the first data set as candidate matching objects of the second target data to construct a second candidate matching queue for each second target data, wherein the first matching objects of the second target data are the candidate matching objects with the smallest difference degree with the second target data in the second candidate matching queue, K is a positive integer, and the value of K is smaller than the number of the target data included in each data set; and
and determining the first target data and the second target data which are first matching objects to be target data pairs which are matched with each other and are adapted to the same target until each first target data is matched or the first candidate matching queue is empty.
In some optional embodiments, the step of determining the first target data and the second target data which are first matching objects to each other as target data pairs which match each other and are adapted to the same target includes:
when the first candidate matching queue is not empty, executing a first matching step:
judging whether the following conditions are met: the first matching object of the first target data is second target data and the first matching object of the second target data is first target data, if yes, the first target data and the second target are matched with each other and are adapted to the same target, and if not, a second matching step is executed on the first matching object of the first target data;
when the second candidate matching queue is not empty, executing a second matching step:
judging whether the following conditions are met: and if the first target data and the second target data are matched with each other and are matched with the same target, executing a first matching step on the first matching object of the second target data.
In some optional embodiments, after performing the second matching step on the first matching object of the first target data, removing the first matching object of the first target data from the first candidate matching queue of the first target data so as to update the first candidate matching queue; after performing the first matching step on the first matching object of the second target data, the first matching object of the second target data is removed from the second candidate matching queue of the second target data, so as to update the second candidate matching queue.
In some optional embodiments, before performing the first matching step, if the first candidate matching queue of the first target data is empty or the first target data has second target data that match each other, the performing of the first matching step on the first target data is stopped, and the performing of the first matching step on another first target data in the first data set is stopped.
In some optional embodiments, the method of updating the first candidate matching queue comprises: updating the candidate matching object with the minimum difference degree with the first target data in the first candidate matching queue as a first matching object; the method for updating the second candidate matching queue comprises the following steps: and updating the candidate matching object with the minimum difference degree with the second target data in the second candidate matching queue as the first matching object.
In some optional embodiments, the method of constructing the first candidate match queue of the first target data comprises: arranging a plurality of second target data from small to large according to the difference degree between the second target data and the first target data, and selecting K second target data as candidate matching objects of the first target data; the method for constructing the second candidate matching queue of the second target data comprises the following steps: and arranging the plurality of first target data from small to large according to the difference degree between the plurality of first target data and the second target data, and selecting K first target data as candidate matching objects of the second target data.
In some optional embodiments, in the first candidate matching queue of each first target data, the degree of difference between each candidate matching object and the first target data is not greater than a predetermined threshold; in the second candidate matching queue of each second target data, the degree of difference between each candidate matching object and the second target data is not larger than a preset threshold value.
In some alternative embodiments, the degree of difference is characterized using the result of one or more of the distance difference, the velocity difference, and the angle difference.
In some alternative embodiments, the degree of difference is characterized by a weighted sum of absolute values of the distance difference, the velocity difference, and the angle difference.
In some optional embodiments, the step of obtaining a first data set comprising a plurality of first target data and a second data set comprising a plurality of second target data comprises: acquiring adjacent first frame echo data and second frame echo data; performing Fourier transform on the first frame of echo data to obtain the distance and the speed corresponding to each first target data; performing Fourier transform on the second frame of echo data to obtain the distance and the speed corresponding to each second target data; and arranging the plurality of first target data according to the numerical sequence of the distance and/or the speed to obtain the first data set, and arranging the plurality of second target data to obtain the second data set.
In a second aspect, the present disclosure also provides a method for target matching, including: respectively converging target data contained in each frame unit in the echo signal into a data set based on at least one target characteristic parameter; constructing a candidate matching target list of each target data; adapting two target data matched with each other to the same target based on the candidate matching target list; and the two target data which are matched with each other are respectively positioned in the data sets which respectively correspond to the two adjacent frame units.
In some optional embodiments, the target characteristic parameter includes a distance, a velocity, a direction angle, and/or an echo energy.
In some optional embodiments, the method further comprises: the updating list is used for removing the two target data which are matched with each other from the candidate matching target list corresponding to the target data except the two target data; and the re-matching is used for adapting two target data which are matched with each other and are except the two target data to the same target after the step of updating the list is executed, and the updating list and the re-matching are sequentially and circularly executed until two target data which are matched with each other do not exist between the candidate matching target lists corresponding to the target data which are not matched after the step of updating the list.
In some optional embodiments, the method further comprises: aiming at any target data, acquiring a difference value between each target data and the target data in a data set corresponding to adjacent frame units based on a preset difference degree function; and constructing the candidate matching target list of the target data according to the difference value.
In some optional embodiments, the constructing the candidate matching target list of the target data according to the difference value includes: selecting K target data from the data sets corresponding to the adjacent frame units of the target data as candidate matching target data according to the sequence of the difference values from small to large; constructing the candidate matching target list based on the K target data; and the difference value between the two target data matched with each other in the candidate matching target list is minimum, and K is a positive integer.
In some optional embodiments, the constructing the candidate matching target list of the target data according to the difference value further includes: filtering target data in a data set corresponding to adjacent frame units of the target data based on a preset target characteristic parameter threshold; and selecting the K target data from the filtered data set as the candidate matching target data corresponding to the target data.
In some optional embodiments, between the updating the list and the re-matching, the method further comprises: and selecting target data for supplementing to each candidate matching target list from the filtered data set according to the sequence of the difference values from small to large, so that the number of the target data contained in the candidate matching target list corresponding to each target data except the two target data is less than or equal to K.
In some optional embodiments, the step of aggregating the target data contained in each frame unit in the echo signal into one data set based on at least one target characteristic parameter includes: processing data of each frame unit to obtain each target data in the frame unit and at least one target characteristic parameter corresponding to each target data; and arranging the target data corresponding to each frame unit according to the numerical sequence of the at least one target characteristic parameter to obtain a data set corresponding to the frame unit.
In a third aspect, the present disclosure also provides a radar system, including: an antenna module adapted to radiate radar signals and receive echoes; and a processor configured to perform the object matching method as claimed in any of the present applications.
In some optional embodiments, the radar system further comprises a memory for sequentially storing each of the target data in each data set according to a parameter value of the target data contained in the data set.
In some alternative embodiments, the present application further provides an integrated circuit, which may include:
the signal transceiving channel is used for transmitting a radio signal and receiving an echo signal; and
a processing module configured to perform a target matching method as defined in any one of the above on the basis of the echo signals.
In some optional embodiments, the integrated circuit may further include a memory for sequentially storing each of the target data in each data set according to a parameter value of the target data included in the data set.
In some optional embodiments, the integrated circuit is a millimeter wave radar chip.
In some optional embodiments, the present application further provides a radio device, which may include:
a carrier;
an integrated circuit as claimed in any preceding claim, disposed on a carrier;
an Antenna disposed on the carrier, or an AiP (Antenna-in-Package) chip integrated with the integrated circuit disposed on the carrier;
the integrated circuit is connected with the antenna through the signal transceiving channel and is used for transmitting the radio signal and receiving the echo signal.
In some optional embodiments, the present application further provides an apparatus, which may comprise:
an apparatus body; and
the radio device as described above provided on the apparatus body;
wherein the radio may be used for object detection and/or communication.
According to the target matching method, the integrated circuit, the radio device and the equipment, the total time complexity of constructing the first candidate matching queue for all the first target data is O (M), and the total time complexity of constructing the second candidate matching queue for all the second target data is O (N); since the number of candidate matching objects per first target data and second target data is limited (not greater than the positive integer K), and the first matching step and the second matching step have a small search amount of data and a small repeated search amount of data, the time complexity of matching M first target data is about o (M). Therefore, the time complexity and the target number of the target matching method are in a linear relation, and the method can ensure the real-time performance of target detection; in addition, compared with the traditional data association method, the method has no complex operation and is suitable for the programming realization of the CPU. The target matching method can reduce the power consumption of the device and improve the operation speed.
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The above and other objects, features and advantages of the present invention will become more apparent from the following description of the embodiments of the present invention with reference to the accompanying drawings, in which:
FIG. 1 shows a flow diagram of a target matching method according to an embodiment of the invention;
FIG. 2 is a schematic diagram illustrating candidate matching objects of a first target data according to an embodiment of the invention;
FIG. 3 is a diagram illustrating a first candidate match queue and a second candidate match queue according to an embodiment of the invention;
FIG. 4 is a diagram illustrating updating a first candidate match queue according to an embodiment of the invention;
FIGS. 5a to 5c respectively show a flow chart of a target matching method according to another embodiment of the present invention;
fig. 6 shows a schematic structural diagram of a radio device according to an embodiment of the present invention.
Detailed Description
The invention will be described in more detail below with reference to the accompanying drawings. Like elements in the various figures are denoted by like reference numerals. For purposes of clarity, the various features in the drawings are not necessarily drawn to scale. Moreover, certain well-known elements may not be shown in the figures.
In the following description, numerous specific details of the invention, such as structure, materials, dimensions, processing techniques and techniques of the devices are described in order to provide a more thorough understanding of the invention. However, as will be understood by those skilled in the art, the present invention may be practiced without these specific details.
For ease of understanding, the following detailed description will be given with reference to a common radar as an example of a sensor:
the radar is a device for finding a target and measuring the space position of the target by using a wireless communication technology, and a modern radar generally comprises two important components, namely a radar signal processing system and a radar data processing system, wherein the radar data processing system carries out calculations such as interconnection, tracking, filtering, smoothing, prediction and the like on target position and motion parameter data (such as radial distance, radial speed, azimuth and the like) of echo data of the radar to form a track of the target.
Tracking of multiple targets is an important research direction in radar systems, wherein the interconnection of target data requires the establishment of a relationship between radar measurement data at a certain moment and measurement (or track) at other moments to determine whether the measurement data come from the same target. For example, in a Linear Frequency Modulation Continuous Wave (LFMCW) radar, the radar continuously transmits a plurality of frames of transmission signals, each frame of transmission signal includes a plurality of same chirps, the transmission signals are reflected by a target object to form an echo, the radar receives the echo and processes each frame of echo to obtain data representing information such as distance, speed, direction, echo energy and the like of the target object, and then the radar generally needs to perform data processing operations such as target tracking, speed ambiguity elimination and the like on each obtained frame of data. Since each frame of data contains information of a plurality of objects, data interconnection is required before data processing, that is, a pair of object information corresponding to the same object is found from the object information output from two frames. In many application scenarios, for example, in an automobile radar, the number of targets corresponding to each frame of data is large, for example, several tens to hundreds, and therefore, it is necessary to establish a matching relationship between multiple targets of two frames of data within a short time (for example, several tens of milliseconds) after the end of each frame of data acquisition, which puts a high requirement on the real-time performance of a matching algorithm.
Therefore, a Data Association method based on statistical theory can be used for matching and Tracking Multiple targets, and the classical methods include Joint Probabilistic Data Association (JPDA), multi-Hypothesis Tracking (MHT), and the like. However, the above method has at least the following disadvantages: (1) the computational complexity is high, such as involving matrix operations; (2) the time complexity is high, and as the number of targets increases, the runtime is significantly increased.
Therefore, the application provides a new target matching method to reduce the computation complexity and the time complexity, thereby reducing the power consumption of the radar system and improving the operation speed of the radar system.
The following is a detailed description of an FMCW radar system as an example:
when an FMCW radar system continuously transmits multiple frames of radar signals to perform target detection, each frame of radar signal includes, for example, multiple identical chirp signals (chirp), and each frame of echo is subjected to two-dimensional Fast Fourier Transform (2D-FFT), Constant False Alarm Rate (CFAR) search, Direction of Arrival (DoA) estimation, and other processing to obtain information of distance, speed, Direction, echo energy, and the like of a target. The radar system has functions of tracking a target, eliminating speed ambiguity, and the like, and before executing the functions, a pair of target information corresponding to the same target (or the closest target) needs to be found from two frames of target information, that is, target matching between the two frames of target information needs to be performed.
Assume that A, B target data sets output for two frames are TA ═ { a1, a2, …, AM }, TB ═ B1, B2, …, BN }, respectively, and M, N are the target data numbers in A, B target data for two frames, respectively. For two different sets of target data Am and Bn, the degree of difference between them is expressed as D (Am, Bn) in the form of a function, and the degree of difference and the degree of matching are in a negative correlation relationship. The purpose of performing target matching is to find out two sets of matched target data in the two sets of sets TA and TB as much as possible, and after all matching relationships are established, the sum of corresponding difference degrees is minimum.
According to the target matching method, the first candidate matching queue and the second candidate matching queue are constructed to perform target matching on the first target data and the second target data, so that the calculation complexity and the time complexity are reduced, the power consumption of a device is reduced, and the running speed is increased.
The following detailed description of embodiments of the present invention is provided in connection with the accompanying drawings and examples.
FIG. 1 shows a flow diagram of a target matching method according to an embodiment of the invention; FIG. 2 is a schematic diagram illustrating candidate matching objects of a first target data according to an embodiment of the invention; FIG. 3 is a diagram illustrating a first candidate match queue and a second candidate match queue according to an embodiment of the invention; FIG. 4 is a diagram illustrating updating a first candidate match queue according to an embodiment of the invention.
For clarity, only two-frame echo target matching method is shown in fig. 1, and it should be understood that, for a data stream containing multiple frames (or multiple signal units) of target information, the steps shown in fig. 1 are repeatedly executed multiple times, i.e. target matching can be continuously performed on multiple frames of target information. In this implementation, the two-frame echoes shown in fig. 1 may be two adjacent frame units in the echo signal, or may be two non-adjacent frame units in which matching target data may exist.
In step S101, a first data set including a plurality of first target data and a second data set including a plurality of second target data are obtained. In this step, two frames of data signals are obtained by performing data processing on two frames of echoes, the two frames of data signals being a first data set including a plurality of first target data and a second data set including a plurality of second target data, respectively. For example, a radar system continuously transmits multi-frame radar signals to detect surrounding objects in real time, each frame of radar signal forms an echo through reflection of a plurality of targets, and after the radar system receives the multi-frame echoes, the multi-frame echoes are subjected to data processing, so that multi-frame data (i.e., a plurality of frame units) are obtained, and each frame of data contains target data of the plurality of targets. In the subsequent steps, object matching is required to be performed on two frames of data, and for the sake of clarity, object data included in one frame of data and corresponding to a plurality of objects respectively are referred to as first object data, and object data included in the other frame of data and corresponding to a plurality of objects respectively are referred to as second object data.
As an example, data included in each frame unit in the echo signal may be subjected to data processing to obtain target data in the frame unit and at least one target characteristic parameter corresponding to the target data; and arranging the target data contained in each frame unit according to the numerical sequence of at least one target characteristic parameter to obtain a data set corresponding to the frame unit. The data processing is, for example, signal processing operations such as a two-dimensional Fast Fourier Transform (2D-FFT), a Constant False Alarm Rate (CFAR) algorithm and/or a Direction Of Arrival (DoA) algorithm, and the target characteristic parameters may include parameters such as a distance, a speed, an Arrival angle, and/or echo energy, and may specifically be types and numbers Of adaptive adjustment parameters according to actual requirements.
In step S102, for each first target data in the first data set, at most K second target data in the second data set are selected as candidate matching objects of the first target data, so as to construct a first candidate matching queue (i.e., a candidate matching object list corresponding to the first target data) for each first target data, where the first matching object of the first target data is a candidate matching object with the smallest degree of difference from the first target data.
In this step, the method of constructing the first candidate matching queue of the first target data includes: and arranging the plurality of second target data from small to large according to the difference degree between the plurality of second target data and the first target data, and selecting K second target data as candidate matching objects of the first target data. Alternatively, the value of K is, for example, 3 or 4. As shown in fig. 2, the difference degrees D (a1, B1) to D (a1, BN) between the first target data a1 and all the second target data B1 to BN are obtained, and after sorting the difference degrees D (a1, B1) to D (a1, BN) from small to large, 3 second target data corresponding to the smallest 3 difference degree functions are selected as candidate matching objects of the first target data a1, in this example, the second target data B1 to B3 are selected as candidate matching objects of the first target data a1, and the difference degrees D (a1, B1), D (a1, B2), D (a1, B3) are 890, 760, 1000 respectively, and when constructing the first candidate matching queue of the first target data a1, the candidate matching queue is sorted from small to large according to the difference degrees, and the first candidate matching queue is shown in a dashed box in fig. 2.
In step S103, for each second target data in the second data set, at most K first target data in the first data set are selected as candidate matching objects of the second target data, so as to construct a second candidate matching queue (i.e., a candidate matching object list corresponding to the second target data) for each second target data, where the first matching object of the second target data is a candidate matching object with the smallest degree of difference from the second target data. In this step, the method of constructing a second candidate matching queue for second target data includes: and arranging the plurality of first target data from small to large according to the difference degree between the plurality of first target data and the second target data, and selecting K first target data as candidate matching objects of the second target data. The method for constructing the second candidate matching queue of the second target data is substantially the same as the method for constructing the first candidate matching queue of the first target data, and is not repeated herein.
As an example, steps S102 and S103 may be performed according to a data receiving order of the first data set and the second data set, for example, the radar system sequentially receives and processes the first frame echo and the second frame echo, and sequentially obtains the first data set and the second data set, and then sequentially constructs a first candidate matching queue for each first target data of the first data set and a second candidate matching queue for each second target data of the second data set. In other alternative examples, since the algorithm of step S102 and step S103 is simple and takes a short time, step S102 and step S103 may be considered to be performed simultaneously. It should be understood that the present application does not limit the sequence of step S102 and step S103.
As shown in FIG. 3, in step S102 and step S103, a first candidate match queue of the first target data A1-AM and a second candidate match queue of the second target data B1-BN are constructed, the first candidate match queue and the second candidate match queue being shown inside the dashed box. In the embodiment of the present invention, the total time complexity of constructing the first candidate matching queue for all the first target data is o (m), and the total time complexity of constructing the second candidate matching queue for all the second target data is o (n).
In the embodiment of the present invention, in step S102 and step S103, the degree of difference is characterized by using, for example, the operation result of one or more of the distance difference, the speed difference, and the angle difference. For example, for the first target data, the distance is represented by R (a, m), the velocity is represented by V (a, m), and the direction angle with respect to the radar is represented by Ang (a, m); for the second target data, its distance is represented by R (B, m), its velocity is represented by V (B, m), and its direction angle with respect to the radar is represented by Ang (B, m). The function D (Am, Bn) of the degree of difference is defined according to the above information, for example, in the following manner:
D(Am,Bn)＝w1*|R(A,m)-R(B,n)|+w2*|V(A,m)-V(B,n)|+w3*|Ang(A,m)-Ang(B,n)|
wherein w1, w2 and w3 are weight coefficients of the distance difference, the speed difference and the angle difference in the difference degree function D (Am, Bn), respectively. Alternatively, the value of the weight coefficient may be adjusted according to the expected state of the target or the state of the radar system, for example, the weight coefficient corresponding to the speed difference may be increased for a target or a radar system in a moving state.
In an alternative embodiment, in the first candidate matching queue of each first target data, the degree of difference between each candidate matching object and the first target data needs to be not greater than a predetermined threshold, and in the second candidate matching queue of each second target data, the degree of difference between each candidate matching object and the second target data needs to be not greater than the predetermined threshold, so as to limit the range of data search in the matching process, and thus reduce the time needed for matching. That is, the second target data in the second data set may be filtered based on a preset target characteristic parameter threshold, so that K second target data are selected from the filtered data set as a first candidate matching queue of a certain first target data. For example, the predetermined thresholds for the distance difference, the speed difference, and the angle difference are set to Rth, Vth, and Angth, respectively, and after the first candidate matching queue for reading and storing the first target data, each candidate matching object in the first candidate matching queue needs to satisfy the following conditions at the same time:
as an example, in step S102 and step S103, the first target data is subjected to two-dimensional fast fourier transform processing to obtain a distance R (a, m) and a velocity V (a, m) of the first target data, and the second target data is subjected to two-dimensional fast fourier transform processing to obtain a distance R (B, m) and a velocity V (B, m) of the second target data. The two-dimensional fast Fourier transform processing is beneficial to reading and storing the first target data and the second target data according to the sequence of the distance from small to large and the speed from small to large, and the storage mode can reduce the data access times of the memory in the matching process.
As an example, the filtered first data set may be used to supplement a second candidate match queue corresponding to second target data, such that, after one or more second target data in the second candidate match queue are removed due to being matched, the number of removed target data items in the second candidate match queue may be supplemented to a value less than/equal to K. The supplementing step may also use the first target data in the second candidate matching queue of the second target data that is not matched and has not been listed in the first data set after filtering as the tail item of the second candidate matching queue in order of decreasing degree of difference.
Similarly, the filtered second data set may be used to supplement a first candidate match queue corresponding to the first target data, such that, after one or more first target data in the first candidate match queue are removed due to being matched, the number of target data items in the first candidate match queue may be supplemented to a value less than/equal to K. The supplementing step may also use, in order from a large degree of difference to a small degree of difference, second target data in the first candidate matching queue of the first target data that is not matched and has not been listed in the filtered second data set as a tail entry of the first candidate matching queue.
In step S104, the first target data and the second target data that are the first matching objects to each other are determined as the first target data and the second target data that match each other until each of the first target data is matched or the first candidate matching queue thereof is empty.
In this step, the method of determining first target data and second target data that are first matching objects for each other as the first target data and second target data that match each other includes: when the first candidate matching queue is not empty, executing a first matching step: judging whether the following conditions are met: the first matching object of the first target data is second target data and the first matching object of the second target data is the first target data, if yes, the first target data and the second target data are matched with each other, and if not, a second matching step is executed on the first matching object of the first target data; when the second candidate matching queue is not empty, executing a second matching step: judging whether the following conditions are met: and if the first matching object of the second target data is the first target data and the first matching object of the first target data is the second target data, matching the first target data and the second target data with each other, and if the first matching object of the second target data is not the second target data, executing a first matching step on the first matching object of the second target data.
In an alternative embodiment, after performing the second matching step on the first matching object of the first target data, if the first candidate matching queue is not empty, the first matching object of the first target data is removed from the first candidate matching queue of the first target data and the first candidate matching queue is updated, and after performing the first matching step on the first matching object of the second target data, if the second candidate matching queue is not empty, the first matching object of the second target data is removed from the second candidate matching queue of the second target data and the second candidate matching queue is updated.
In this embodiment, before performing the first matching step, if the first candidate matching queue of the first target data is empty or the first target data has second target data that match each other, the performing of the first matching step on the first target data is stopped, and the first matching step is performed on another first target data in the first data set.
Optionally, before performing the first/second matching step, if the first/second candidate matching queue of the first/second target data is empty or the first/second target data has the second/first target data matching with each other, the first/second target data and the first/second candidate matching queue thereof are removed from the first/second data set.
Optionally, the method for updating the first candidate matching queue includes: updating the candidate matching object with the minimum difference degree with the first target data in the first candidate matching queue as a first matching object; the method for updating the second candidate matching queue comprises the following steps: and updating the candidate matching object with the minimum difference degree with the second target data in the second candidate matching queue as the first matching object. As shown in fig. 4, the method for updating the first candidate matching queue includes: for the first target data a1, the candidate matching objects thereof include a first matching object Bn1, a second matching object Bn2 and a third matching object Bn3, the degree of difference between the first matching object Bn1, the second matching object Bn2 and the third matching object Bn3 and the first target data a1 are arranged from small to large, if the first matching object B1 is removed, the candidate matching object remaining in the first candidate matching queue with the smallest degree of difference from the first target data a1 is Bn2, and then the second matching object Bn2 is updated to be the new first matching object of the first target data a 1.
In step S104, since the number of candidate matching objects per first target data and second target data is limited (not greater than the positive integer K), and the matching step shown in step S104 has a small search amount for data and a small amount of repeatedly searched data, the time complexity of matching M first target data is about o (M).
Fig. 5a to 5c respectively show a flow chart of a target matching method according to another embodiment of the present invention. Wherein fig. 5b shows a flowchart of a first matching step pair a () in the target matching method, and fig. 5b shows a flowchart of a second matching step pair b () in the target matching method.
In step S201, a first candidate matching queue of first target data and a second candidate matching queue of second target data are constructed. This step can refer to steps S101 to S103 in fig. 1, and the same parts are not described herein again.
In step S202, the initial value of the number M of the first target data is set to 0, and the total number of the first target data is set to M.
In step S203, the sequence number m of the first target data is updated to m plus one.
In step S204, it is determined whether M is greater than M, and if yes, the target matching is ended, and if no, step S204 is performed.
In step S205, it is determined whether: the mth first target data Am already has the second target data matching each other or the first candidate matching queue thereof is empty, if yes, the process returns to perform step S202, and if no, the first matching step pair () is performed on the first target data Am, the first matching step pair () including steps S211 to S217.
In step S211, it is determined whether: the mth first target data Am already has the second target data matching each other or the first candidate matching queue thereof is empty, if yes, step S212 is executed, the execution of the first matching step pair () is ended, and the output result that the mth first target data Am already has the second target data matching each other or the first candidate matching queue thereof is empty, if no, step S213 is executed.
In step S213, a first matching object Bn of the first target data Am is obtained.
In step S214, it is determined whether or not the first matching object of the second target data Bn is the first target data Am, and if so, step S215 is executed to determine that the first target data Am and the second target data Bn match each other, and to end execution of the first matching step pair () which includes steps S221 to S227, and if not, the second matching step pair () is executed on the second target data Bn.
After the execution of the second matching step pair () is finished, in step S216, it is determined whether the first target data Am has second target data that match each other, and if so, step S211 is repeatedly executed, and if not, step S217 is executed, the second target data Bn is removed from the first candidate matching queue of the first target data Am, and then step S211 is repeatedly executed.
The second matching step pair b () is substantially the same as the first matching step pair a () except that the first target data Am and the second target data Bn in each step are interchanged. Specifically, in step S221, it is determined whether: the nth second target data Bn has already had the first target data matching each other or the second candidate matching queue thereof is empty, if yes, step S222 is performed, the execution of the second matching step pair () is ended, and the result is output that the nth second target data Bn has already had the first target data matching each other or the second candidate matching queue thereof is empty, if no, step S223 is performed.
In step S223, the first matching object Am of the second target data Bn is obtained.
In step S224, it is determined whether the first matching object of the first target data Am is the second target data Bn, and if so, step S235 is executed, the first target data Am and the second target data Bn are determined to match each other, and execution of the second matching step pair () is ended, and if not, the first matching step pair a () is executed, the first matching step pair a () including steps S211 to S217.
After the execution of the first matching step pair a () is finished, in step S226, it is determined whether the second target data Bn has mutually matched first target data, if yes, step S221 is repeatedly executed, if no, step S227 is executed, the first target data Am is removed from the second candidate matching queue of the second target data Bn, and then step S221 is repeatedly executed.
In the above step, the total time complexity of constructing the first candidate matching queue for all the first target data is o (m), and the total time complexity of constructing the second candidate matching queue for all the second target data is o (n); since the number of candidate matching objects per first target data and second target data is limited (not greater than the positive integer K), and the first matching step and the second matching step have a small search amount of data and a small repeated search amount of data, the time complexity of matching M first target data is about o (M).
In combination with the analysis, the time complexity and the target number of the target matching method are in a linear relation, and the method can ensure real-time performance; in addition, compared with the traditional data association method, the method has no complex operation and is suitable for the programming realization of the CPU.
In one embodiment, the present application further provides an integrated circuit having a signal transceiving channel and a processing module, the signal transceiving channel being operable to transmit a radio signal and receive an echo signal reflected by a target; the processing module may be configured to perform operations such as analog signal processing, analog-to-digital conversion, digital signal processing, etc. on the echo signal, and may be configured to perform relevant steps of the target matching method as set forth in any embodiment of the present application based on the digital signal output by the digital signal processing operation.
In some optional embodiments, the integrated circuit may further comprise a memory for sequentially storing each of the target data in each data set according to a parameter value of the target data contained in the data set. In addition, the integrated circuit can be a sensor chip, such as a millimeter wave radar chip, and the like, and can also be an AiP chip structure based on a package antenna.
According to the integrated circuit, the candidate target matching list is constructed according to the arrangement sequence of the preset parameters, the matching process is executed based on the set threshold, the operation amount of target matching between two frames of signals in the target detection process can be effectively reduced, the flexible candidate target list and the flexible matching process can be constructed through programming, and the timeliness of operations such as target tracking, fuzzy speed elimination and the like is further improved.
In one embodiment, the present application also provides a radio device comprising: a carrier; the integrated circuit of the above embodiment is disposed on the carrier; an antenna disposed on the carrier; the integrated circuit is connected with the antenna through a first transmission line and used for receiving and transmitting radio signals, the carrier body can be a Printed Circuit Board (PCB), and the first transmission line can be a PCB wiring line. In addition, for the AiP structure integrated circuit, there is no need to provide an antenna structure on the carrier.
Fig. 6 shows a schematic diagram of a radio device according to an embodiment of the invention.
As shown in fig. 6, the radio device 100 includes an antenna module 110 and an integrated circuit 120. The antenna module 110 includes a transmitting antenna 111 and a receiving antenna 112, and the radio device 120 includes a radio frequency module 121 and a processing module 122.
The transmitting antenna 111 receives a radar signal (for example, a chirp continuous wave) transmitted by the rf module 121, and radiates multiple frames of detection signals to the surroundings, where each frame of detection signal forms a frame of echo through reflection of multiple targets.
The receiving antenna 112 receives the multi-frame echo, the processing module 122 performs data processing on the multi-frame echo, and the processing module 122 includes, for example, a two-dimensional fast fourier transform unit, a constant false alarm rate unit, an arrival angle estimation unit, and the like, so as to obtain information such as a distance, a speed, a direction, echo energy, and the like of the target.
In the embodiment of the present invention, the processing module 122 is further configured to execute a target matching method as shown in fig. 1 or fig. 5a to 5c, so as to complete target matching on multiple target data represented by multiple echoes, so that the radar system has functions of target tracking, speed ambiguity elimination, and the like.
The radio device 100 may further comprise a memory (not shown) for sequentially storing the respective target data in each data set according to their included parameter values (e.g. speed and/or distance), thereby reducing the number of memory accesses during the target matching process. Such as the memory of the integrated circuit 120.
In addition, the antenna module 110 may also be integrated in a package of the integrated circuit module 120 to form a chip of AiP structure, such as a sensor chip, for example, a millimeter wave radar chip.
In one embodiment, the present application further provides an apparatus comprising: an apparatus body; and a radio device as in the above embodiment provided on the apparatus body; wherein the radio device is used for object detection and/or communication functions.
Specifically, on the basis of the above-described embodiments, in one embodiment of the present application, the radio device may be provided outside the apparatus body, in another embodiment of the present application, the radio device may be provided inside the apparatus body, and in other embodiments of the present application, the radio device may be provided partly inside the apparatus body and partly outside the apparatus body. The present application is not limited thereto, as the case may be.
It should be noted that the radio device can perform functions such as object detection and communication by transmitting and receiving signals.
In an optional embodiment, the device body may be an intelligent transportation device (such as an automobile, a bicycle, a motorcycle, a ship, a subway, a train, etc.), a security device (such as a camera), an intelligent wearable device (such as a bracelet, glasses, etc.), an intelligent home device (such as a television, an air conditioner, an intelligent lamp, etc.), various communication devices (such as a mobile phone, a tablet computer, etc.), and various devices such as a barrier gate, an intelligent transportation indicator lamp, an intelligent sign, a transportation camera, various industrial manipulators (or a robot), and various instruments for detecting vital sign parameters and various devices carrying the instruments. The radio device may be a radio device as set forth in any embodiment of the present application, and the structure and the operation principle of the radio device have been described in detail in the above embodiments, which are not described in detail herein.
While embodiments in accordance with the invention have been described above, these embodiments are not intended to be exhaustive or to limit the invention to the precise embodiments described. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention and various embodiments with various modifications as are suited to the particular use contemplated. The invention is limited only by the claims and their full scope and equivalents.
Claims (23)
1. A method of object matching, comprising:
obtaining a first data set comprising a plurality of first target data and a second data set comprising a plurality of second target data;
for each first target data in a first data set, selecting at most K second target data in a second data set as candidate matching objects of the first target data to construct a first candidate matching queue for each first target data, wherein the first matching object of the first target data is the candidate matching object with the smallest difference degree with the first target data in the first candidate matching queue;
for each second target data in a second data set, selecting at most K first target data in the first data set as candidate matching objects of the second target data to construct a second candidate matching queue for each second target data, wherein the first matching object of the second target data is a candidate matching object with the smallest difference degree with the second target data in the second candidate matching queue, and K is a positive integer; and
and determining the first target data and the second target data which are first matching objects to be target data pairs which are matched with each other and are adapted to the same target until each first target data is matched or the first candidate matching queue is empty.
2. The target matching method according to claim 1, wherein the step of determining first target data and second target data that are first matching objects of each other as a pair of target data that match each other and are adapted to the same target comprises:
when the first candidate matching queue is not empty, executing a first matching step:
judging whether the following conditions are met: the first matching object of the first target data is second target data and the first matching object of the second target data is first target data, if yes, the first target data and the second target are matched with each other and are adapted to the same target, and if not, a second matching step is executed on the first matching object of the first target data;
when the second candidate matching queue is not empty, executing a second matching step:
judging whether the following conditions are met: and if the first target data and the second target data are matched with each other and are matched with the same target, executing a first matching step on the first matching object of the second target data.
3. The object matching method according to claim 2,
removing the first matching object of the first target data from the first candidate matching queue of the first target data after performing the second matching step on the first matching object of the first target data to update the first candidate matching queue,
after performing the first matching step on the first matching object of the second target data, the first matching object of the second target data is removed from the second candidate matching queue of the second target data, so as to update the second candidate matching queue.
4. The object matching method according to claim 2,
before the first matching step is performed, if a first candidate matching queue of a first target data is empty or the first target data has a second target data matching each other, the first matching step is stopped from being performed on the first target data, and the first matching step is performed on another first target data in the first data set.
5. The object matching method according to claim 3,
the method for updating the first candidate matching queue comprises the following steps: updating the candidate matching object with the minimum difference degree with the first target data in the first candidate matching queue as a first matching object;
the method for updating the second candidate matching queue comprises the following steps: and updating the candidate matching object with the minimum difference degree with the second target data in the second candidate matching queue as the first matching object.
6. The object matching method according to claim 1,
the method for constructing the first candidate matching queue of the first target data comprises the following steps: arranging a plurality of second target data from small to large according to the difference degree between the second target data and the first target data, selecting K second target data as candidate matching objects of the first target data,
the method for constructing the second candidate matching queue of the second target data comprises the following steps: and arranging the plurality of first target data from small to large according to the difference degree between the plurality of first target data and the second target data, and selecting K first target data as candidate matching objects of the second target data.
7. The object matching method according to claim 6,
in the first candidate matching queue of each first target data, the degree of difference between each candidate matching object and the first target data is not more than a preset threshold value,
in the second candidate matching queue of each second target data, the degree of difference between each candidate matching object and the second target data is not larger than a preset threshold value.
8. The object matching method according to claim 6, characterized in that the degree of difference is characterized using the result of one or more of distance difference, velocity difference and angle difference.
9. The method of object matching according to claim 8, characterized in that the degree of difference is characterized by a weighted sum of absolute values of distance difference, velocity difference and angle difference.
10. The object matching method according to any one of claims 1-9, wherein the step of obtaining a first data set comprising a plurality of first object data and a second data set comprising a plurality of second object data comprises:
acquiring adjacent first frame echo data and second frame echo data;
performing Fourier transform on the first frame of echo data to obtain the distance and the speed corresponding to each first target data;
performing Fourier transform on the second frame of echo data to obtain the distance and the speed corresponding to each second target data;
and arranging the plurality of first target data according to the numerical sequence of the distance and/or the speed to obtain the first data set, and arranging the plurality of second target data to obtain the second data set.
11. A method of object matching, the method comprising:
respectively converging target data contained in each frame unit in the echo signal into a data set based on at least one target characteristic parameter;
constructing a candidate matching target list of each target data; and
adapting two target data matched with each other to the same target based on the candidate matching target list;
and the two target data which are matched with each other are respectively positioned in the data sets which respectively correspond to the two adjacent frame units.
12. The method of claim 11, wherein the target characteristic parameters include distance, velocity, direction angle, and/or echo energy.
13. The method of claim 11, further comprising:
the updating list is used for removing the two target data which are matched with each other from the candidate matching target list corresponding to the target data except the two target data;
a re-matching for adapting two target data, which match each other, other than the two target data to the same target after the step of updating the list is performed,
and the updating list and the re-matching are sequentially and circularly executed until two target data which are matched with each other do not exist between the candidate matching target lists corresponding to the target data which are not matched after the step of updating the list.
14. The method of claim 13, further comprising:
aiming at any target data, acquiring a difference value between each target data and the target data in a data set corresponding to adjacent frame units based on a preset difference degree function;
and constructing the candidate matching target list of the target data according to the difference value.
15. The method of claim 14, wherein said constructing the candidate matching target list of the target data according to the difference value comprises:
selecting K target data from the data sets corresponding to the adjacent frame units of the target data as candidate matching target data according to the sequence of the difference values from small to large; and
constructing the candidate matching target list based on the K target data;
and the difference value between the two target data matched with each other in the candidate matching target list is minimum, and K is a positive integer.
16. The method of claim 15, wherein the constructing the candidate matching target list of the target data according to the difference value further comprises:
filtering target data in a data set corresponding to adjacent frame units of the target data based on a preset target characteristic parameter threshold; and
and selecting the K target data from the filtered data set as the candidate matching target data corresponding to the target data.
17. The method of claim 16, wherein between the updating the list and the re-matching, the method further comprises:
and selecting target data for supplementing to each candidate matching target list from the filtered data set according to the sequence of the difference values from small to large, so that the number of the target data contained in the candidate matching target list corresponding to each target data except the two target data is less than or equal to K.
18. The method according to any one of claims 11 to 17, wherein the step of aggregating the target data contained in each frame unit in the echo signal into one data set based on at least one target characteristic parameter comprises:
processing data of each frame unit to obtain each target data in the frame unit and at least one target characteristic parameter corresponding to each target data; and
and arranging the target data corresponding to each frame unit according to the numerical sequence of the at least one target characteristic parameter to obtain a data set corresponding to the frame unit.
19. An integrated circuit, comprising:
the signal transceiving channel is used for transmitting a radio signal and receiving an echo signal; and
a processing module configured to perform the target matching method of any of claims 1 to 18 based on the echo signal.
20. The integrated circuit of claim 19, further comprising a memory for sequentially storing each of the target data in each data set according to a parameter value of the target data included in the data set.
21. The integrated circuit of claim 19 or 20, wherein the integrated circuit is a millimeter wave radar chip.
22. A radio device, comprising:
a carrier;
an integrated circuit as claimed in any one of claims 19 to 21, disposed on a carrier;
an antenna disposed on the carrier or AiP die integrated with the integrated circuit disposed on the carrier;
the integrated circuit is connected with the antenna through the signal transceiving channel and is used for transmitting the radio signal and receiving the echo signal.
23. An apparatus, comprising:
an apparatus body; and
the radio of claim 22 disposed on the equipment body;
wherein the radio device is used for object detection and/or communication.
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