CN116644271A - Target object detection method, device, vehicle and medium - Google Patents
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Abstract
The invention discloses a target object detection method, a target object detection device, a vehicle and a medium, wherein the method is applied to the vehicle, and the vehicle is provided with a MIMO millimeter wave radar, and the method comprises the following steps: acquiring echo signals of the MIMO millimeter wave radar, wherein the echo signals are distributed in three dimensions of distance, speed and channel; performing signal processing on the echo signals to obtain processing results, wherein the processing results correspond to two dimensions of distance and speed; and determining a target signal-to-noise ratio of the echo signal in a preset distance range based on the processing result, and detecting whether a target object exists in the preset distance range of the vehicle according to the target signal-to-noise ratio. The method can rapidly realize the detection of the target object on the basis of simplifying the detection method, and improves the real-time performance of the detection.
Description
Technical Field
The present invention relates to the field of millimeter wave radar signal processing technologies, and in particular, to a method, an apparatus, a vehicle, and a medium for detecting a target object.
Background
The arrival of the intelligent age brings more and more new technologies for the automobile intellectualization. In the process of pursuing the intelligence of the vehicle, users are also pursuing the safety and use experience of the vehicle continuously, for example, the vehicle is added with a function of detecting a target object (such as a child) independently remained in the vehicle and giving an alarm to a vehicle owner or an emergency department so as to avoid heatstroke death of the child.
However, the existing radar-based target object detection method is complicated, the target object in the scene cannot be locked quickly, and the real-time performance is poor.
Disclosure of Invention
The invention provides a target object detection method, a target object detection device, a vehicle and a medium, so that the target object can be rapidly detected on the basis of simplifying the detection method, and the real-time performance of the detection is improved.
According to an aspect of the present invention, there is provided a target object detection method applied to a vehicle on which a MIMO millimeter wave radar is mounted, the method including:
acquiring echo signals of the MIMO millimeter wave radar, wherein the echo signals are distributed in three dimensions of distance, speed and channel;
performing signal processing on the echo signals to obtain processing results, wherein the processing results correspond to two dimensions of distance and speed;
and determining a target signal-to-noise ratio of the echo signal in a preset distance range based on the processing result, and detecting whether a target object exists in the preset distance range of the vehicle according to the target signal-to-noise ratio.
According to another aspect of the present invention, there is provided a detection apparatus of a target object, the apparatus being configured to a vehicle, including:
The acquisition module is used for acquiring echo signals of the MIMO millimeter wave radar, wherein the echo signals are distributed in three dimensions of distance, speed and channel;
the signal processing module is used for performing signal processing on the echo signals to obtain processing results, and the processing results correspond to the two dimensions of the distance and the speed;
and the determining module is used for determining the target signal-to-noise ratio of the echo signal in the preset distance range based on the processing result and detecting whether a target object exists in the preset distance range of the vehicle according to the target signal-to-noise ratio.
According to another aspect of the present invention, there is provided a vehicle including:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the method of detecting a target object according to any one of the embodiments of the present invention.
According to another aspect of the present invention, there is provided a computer readable storage medium storing computer instructions for causing a processor to execute the method for detecting a target object according to any one of the embodiments of the present invention.
The embodiment of the invention provides a target object detection method, a target object detection device, a vehicle and a medium, wherein the method is applied to the vehicle, and the vehicle is provided with a MIMO millimeter wave radar, and the method comprises the following steps: acquiring echo signals of the MIMO millimeter wave radar, wherein the echo signals are distributed in three dimensions of distance, speed and channel; performing signal processing on the echo signals to obtain processing results, wherein the processing results correspond to two dimensions of distance and speed; and determining a target signal-to-noise ratio of the echo signal in a preset distance range based on the processing result, and detecting whether a target object exists in the preset distance range of the vehicle according to the target signal-to-noise ratio. By using the technical scheme, the processing result is obtained by carrying out signal processing on the echo signal, the target signal-to-noise ratio of the echo signal in the preset distance range is determined based on the processing result, and whether the target object exists in the preset distance range of the vehicle or not is detected according to the target signal-to-noise ratio, so that the detection of the target object can be rapidly realized on the basis of simplifying the detection method, and the real-time performance of the detection is improved.
It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the invention or to delineate the scope of the invention. Other features of the present invention will become apparent from the description that follows.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flowchart of a method for detecting a target object according to a first embodiment of the present invention;
FIG. 2 is a flowchart of a method for detecting a target object according to a second embodiment of the present invention;
FIG. 3 is a flowchart of another method for detecting a target object according to a second embodiment of the present invention;
FIG. 4 is a schematic diagram of a transformed echo signal according to a second embodiment of the present invention;
FIG. 5 is a schematic diagram of another transformed echo signal provided according to a second embodiment of the present invention;
fig. 6 is a schematic diagram of a preprocessed echo signal according to a second embodiment of the present invention;
FIG. 7 is a schematic diagram of another preprocessed echo signal according to a second embodiment of the present invention;
FIG. 8 is a diagram of a target signal-to-noise ratio provided in accordance with a second embodiment of the present invention;
FIG. 9 is a schematic diagram of another target signal-to-noise ratio provided in accordance with a second embodiment of the present invention;
fig. 10 is a schematic structural diagram of a detection device for a target object according to a third embodiment of the present invention;
fig. 11 is a schematic structural view of a vehicle according to a fourth embodiment of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example 1
Fig. 1 is a flowchart of a method for detecting a target object according to an embodiment of the present invention, where the method may be performed by a target object detection device, and the target object detection device may be implemented in hardware and/or software, and the target object detection device may be configured in a vehicle.
It is considered that radar is used as an important intelligent sensor for sensing not only the environment around the vehicle but also passengers in the vehicle as an important sensor for the intelligent cabin.
At present, a plurality of research institutions at home and abroad develop radar-based target object (such as living body) detection technology, on one hand, the prior art provides a living body detection method, and by detecting the phase of a radar received echo, vital sign information can be obtained through processing, so that the influence of higher harmonic waves and direct current offset caused by I/Q two paths of signals caused by amplitude estimation are avoided. On the other hand, the prior art proposes a vehicle cabin human body detection method that, unlike the conventional non-contact vital sign detection technique in which a radar is mounted in front of a vital body, mounts the radar to a car seat, detects vital sign information by measuring a loss factor of a signal from the back to the chest of a human body, loss factors of various parts to the signal, the type of clothing worn, and the like. However, the detection method cannot quickly lock the living body in the scene, and the effect is general; secondly, the effect of eliminating false targets and other interferences is not satisfactory, and the false alarm is high; for weak moving targets, such as light breath and weak reflection intensity targets, the detection effect of the method is general, and the detection omission is more.
Based on the above, the embodiment of the invention provides a target object detection method, which utilizes the difference of radar signal reflection intensity at the position of the existence of a target to judge whether the target object exists or not, can rapidly realize the detection of the target object, and improves the real-time performance and accuracy of the detection. As shown in fig. 1, the method includes:
s110, acquiring echo signals of the MIMO millimeter wave radar, wherein the echo signals are distributed in three dimensions of distance, speed and channel.
The MIMO millimeter wave radar may be considered as a millimeter wave radar device mounted on a vehicle, and the device may operate in a Multiple-Input Multiple-Output (MIMO) manner, and the type and mounting position of the specific millimeter wave radar device are not limited, and may be set according to actual requirements.
In this embodiment, the MIMO millimeter wave radar may send millimeter wave radar signals in a MIMO manner and receive signals returned by multiple channels, so this embodiment may collect the returned signals to obtain echo signals of the MIMO millimeter wave radar, where the echo signals are distributed in three dimensions of distance, speed and channels, and a specific manner of obtaining echo signals is not limited, for example, the MIMO millimeter wave radar may send chirped continuous wave (Linear Frequency Modulation Continuous Wave, LFMCW) signals in a MIMO manner, and then may mix the signals returned by multiple channels to obtain intermediate frequency signals respectively, and the acquisition board may acquire the intermediate frequency signals according to the nyquist sampling theorem to obtain ADC original data, that is, echo signals. It is considered that the ADC raw data may include information of the target object, and the ADC data is subjected to signal processing to obtain the information of the target object.
And S120, performing signal processing on the echo signals to obtain processing results, wherein the processing results correspond to the two dimensions of the distance and the speed.
Specifically, in this step, the obtained echo signal may be subjected to corresponding signal processing to obtain processing results corresponding to two dimensions of a distance and a speed, which are not described in detail herein, for example, the echo signal may be preprocessed in the dimensions of the distance, the speed and/or the channel, and then the preprocessed signal is subjected to certain processing in the dimensions of the channel to obtain corresponding processing results, where a specific processing means may be set according to an actual situation, and different processing means may correspond to different processing results.
S130, determining a target signal-to-noise ratio of the echo signal in a preset distance range based on the processing result, and detecting whether a target object exists in the preset distance range of the vehicle according to the target signal-to-noise ratio.
The preset distance range may be considered as a preset distance range, in which a target object may exist, for example, the preset distance range may be understood as a distance between the target object and the millimeter wave radar, and the specific numerical value may be determined by a configurator according to an empirical value; the target signal-to-noise ratio may refer to a signal-to-noise ratio of the echo signal within a preset distance range.
Specifically, after the processing result is obtained through the above steps, the target signal-to-noise ratio of the echo signal in the preset distance range can be determined based on the obtained processing result, and whether the target object exists in the preset distance range of the vehicle or not can be detected according to the determined target signal-to-noise ratio, wherein the step of determining the target signal-to-noise ratio is not limited, for example, the target signal-to-noise ratio can be directly obtained based on the processing result, the processing result can be calculated to determine the target signal-to-noise ratio, and the calculation mode is not further expanded, so long as the target signal-to-noise ratio can be obtained.
Further, after the target signal-to-noise ratio is obtained, whether the target object exists in the preset distance range of the vehicle can be detected according to the determined target signal-to-noise ratio, for example, whether the target object exists in the preset distance range of the vehicle can be judged according to the specific size of the target signal-to-noise ratio, so that the detection of the target object is realized.
In one embodiment, the detecting whether a target object exists within a preset distance range of the vehicle according to the target signal-to-noise ratio includes:
detecting whether the target signal-to-noise ratio is greater than a preset signal-to-noise ratio or not to obtain a detection result;
And determining whether the vehicle has a target object within a preset distance range or not based on the detection result.
The preset signal-to-noise ratio may be a preset signal-to-noise ratio, which is used for determining the detection result, the value of the preset signal-to-noise ratio may be an empirical value, and optionally, the preset signal-to-noise ratio may be 1.
In one embodiment, whether the obtained target signal-to-noise ratio is greater than a preset signal-to-noise ratio may be detected to obtain a detection result, and then whether the vehicle has a target object within a preset distance range may be determined based on the obtained detection result. For example, after the target snr is calculated to be 0.8, the target snr may be compared with the preset snr 1 to detect whether the target snr is greater than the preset snr, where the detection result is that the target snr is less than the preset snr, so that the vehicle may be considered to have no target object within the preset distance according to the detection result.
According to the method for detecting the target object, provided by the embodiment of the invention, echo signals of the MIMO millimeter wave radar are obtained, and the echo signals are distributed in three dimensions of distance, speed and channel; performing signal processing on the echo signals to obtain processing results, wherein the processing results correspond to two dimensions of distance and speed; and determining a target signal-to-noise ratio of the echo signal in a preset distance range based on the processing result, and detecting whether a target object exists in the preset distance range of the vehicle according to the target signal-to-noise ratio. According to the method, the processing result is obtained by carrying out signal processing on the echo signal, the target signal-to-noise ratio of the echo signal in the preset distance range is determined based on the processing result, whether the target object exists in the preset distance range of the vehicle or not is detected according to the target signal-to-noise ratio, detection of the target object can be rapidly achieved on the basis of simplifying the detection method, and the real-time performance of detection is improved.
In one embodiment, the determining, based on the processing result, a target signal-to-noise ratio of the echo signal within a preset distance range includes:
determining a first signal strength of the echo signal within a complete distance range based on the processing result;
determining a second signal intensity of the echo signal in a preset distance range based on the processing result;
and calculating the target signal-to-noise ratio of the echo signal in a preset distance range according to the first signal intensity and the second signal intensity.
The complete distance range may be considered as a range of the echo signal in the distance dimension, where the complete distance range includes all amplitude values of the echo signal in the distance dimension, and the preset distance range may be a part of the complete distance range, for example, the preset distance range may be considered as a part of the complete distance range that is of interest in the present embodiment. The first signal strength may refer to a signal amplitude corresponding to a complete distance range of the echo signal in each speed dimension, and the second signal strength may refer to a signal amplitude corresponding to a preset distance range of the echo signal in each speed dimension.
Specifically, the present embodiment may determine a first signal strength of an echo signal within a complete distance range based on a processing result, determine a second signal strength of the echo signal within a preset distance range based on the processing result, and then calculate a target signal-to-noise ratio of the echo signal within the preset distance range according to the obtained first signal strength and the obtained second signal strength.
In one embodiment, the determining the first signal strength of the echo signal over the full range of distances based on the processing result includes:
and processing the processing result in the distance dimension within the complete distance range to obtain the first signal intensity of the echo signal within the complete distance range.
In one embodiment, the processing result may be processed in the distance dimension over the complete distance range to obtain a first signal strength of the echo signal over the complete distance range, e.g., to obtain a first signal strength of the echo signal in each velocity dimension, which may be expressed asWherein X (k, v) is a processing result corresponding to two dimensions of distance and speed, R N The number of samples for a single chirp in the distance dimension.
In one embodiment, the determining, based on the processing result, the second signal strength of the echo signal within a preset distance range includes:
and processing the processing result in the distance dimension within a preset distance range to obtain the second signal intensity of the echo signal within the preset distance range.
In one embodiment, the processing result may be processed in the distance dimension within a preset distance range to obtain a second signal strength of the echo signal within the preset distance range, for example, the second signal strength of the echo signal in each velocity dimension may be expressed as Wherein X (k, v) is a processing result corresponding to two dimensions of distance and speed, r 2 、r 1 The maximum value and the minimum value of the distance unit corresponding to the preset distance range are respectively set.
Example two
Fig. 2 is a flowchart of a target object detection method according to a second embodiment of the present invention, where the second embodiment is optimized based on the above embodiments. In this embodiment, the echo signal is subjected to signal processing, and the processing result is further specified as: preprocessing the echo signals to obtain preprocessed echo signals; and carrying out coherent accumulation processing on the preprocessed echo signals in the channel dimension to obtain processing results.
For details not yet described in detail in this embodiment, refer to embodiment one.
As shown in fig. 2, the method includes:
s210, acquiring echo signals of the MIMO millimeter wave radar, wherein the echo signals are distributed in three dimensions of distance, speed and channel.
S220, preprocessing the echo signals to obtain preprocessed echo signals.
In this embodiment, before the processing result is obtained by calculation, a certain preprocessing may be performed on the echo signal to better perform the calculation of the subsequent processing result, for example, the preprocessing may be performed on the echo signal in one or several dimensions of the distance, the speed and the channel to obtain the preprocessed echo signal, and further, specific preprocessing means may be different according to different dimensions.
In one embodiment, the preprocessing the echo signal to obtain a preprocessed echo signal includes:
performing Fourier transform on the echo signals in a distance dimension to obtain transformed echo signals;
and performing clutter processing on the transformed echo signals to obtain preprocessed echo signals.
Specifically, fourier transformation can be performed on the echo signal in the distance dimension to obtain a transformed echo signal, wherein the obtained frequency spectrum is positively correlated with the distance, and the frequency can be converted into the target distance according to the relation between the frequency spectrum and the distance, so that the distribution condition of the signal on the range profile is obtained; and then clutter processing can be carried out on the transformed echo signals to obtain preprocessed echo signals, for example, clutter corresponding to fixed targets in a scene can be removed through clutter processing, the clutter processing mode is not limited, for example, clutter processing can be carried out through average value cancellation operation in the speed dimension.
S230, carrying out coherent accumulation processing on the preprocessed echo signals in the channel dimension to obtain processing results.
After the preprocessed echo signals are obtained, coherent accumulation processing can be performed on the preprocessed echo signals in the channel dimension to obtain processing results, for example, the data in the same distance unit and speed unit can be accumulated in the channel to obtain processing results corresponding to the two dimensions of the distance and the speed.
S240, determining a target signal-to-noise ratio of the echo signal in a preset distance range based on the processing result, and detecting whether a target object exists in the preset distance range of the vehicle according to the target signal-to-noise ratio.
According to the detection method of the target object, provided by the embodiment II, echo signals of the MIMO millimeter wave radar are obtained, the echo signals are distributed in three dimensions of distance, speed and channel, and the echo signals are preprocessed to obtain preprocessed echo signals; carrying out coherent accumulation processing on the preprocessed echo signals in the channel dimension to obtain processing results; and determining a target signal-to-noise ratio of the echo signal in a preset distance range based on the processing result, and detecting whether a target object exists in the preset distance range of the vehicle according to the target signal-to-noise ratio. By means of the method, the echo signals after pretreatment are obtained, the echo signals after pretreatment are subjected to coherent accumulation treatment in the channel dimension, the treatment result is obtained, the accuracy of the treatment result can be improved, and the real-time performance of detection is improved.
In one embodiment, before the fourier transforming the echo signal in the distance dimension to obtain the transformed echo signal, the method further includes:
Windowing the echo signal in a distance dimension to obtain a windowed echo signal;
performing fourier transform on the echo signal in a distance dimension to obtain a transformed echo signal, including:
and carrying out Fourier transform on the windowed echo signals in a distance dimension to obtain transformed echo signals.
It is considered that before the fourier transform of the echo signal in the distance dimension, the echo signal may be windowed in the distance dimension to obtain a windowed echo signal, and then the fourier transform of the windowed echo signal in the distance dimension may be performed to obtain a transformed echo signal. On the basis, the side lobes of the amplitude-frequency curve in the subsequent Fourier transform can be realized. The method of windowing is not limited and, illustratively, the echo signal may be multiplied along a distance dimension by a sequence of window functions including, but not limited to, rectangular windows, hamming windows, etc. to effect the windowing of the echo signal.
In one embodiment, the clutter processing is performed on the transformed echo signal to obtain a preprocessed echo signal, which includes:
Calculating the average value of the transformed echo signals in the speed dimension;
and determining a preprocessed echo signal based on the transformed echo signal and the mean value.
In one embodiment, the clutter processing of the transformed echo signal may be, for example: the method comprises the steps of firstly calculating the average value of the transformed echo signals in the speed dimension, such as calculating the average value of each speed unit under the same distance unit and the same channel, then determining the preprocessed echo signals based on the transformed echo signals and the average value, and exemplarily, obtaining the preprocessed echo signals by taking the difference between the transformed echo signals and the average value, and calculating the average value of the transformed echo signals and the average value again to serve as the preprocessed echo signals.
Fig. 3 is a flowchart of another method for detecting a target object according to the second embodiment of the present invention, as shown in fig. 3, firstly, acquiring multi-channel ADC data (i.e., acquiring echo signals of the MIMO millimeter wave radar, where the echo signals are distributed in three dimensions of distance, speed and channel), performing fast fourier transform on the distance dimension (performing fourier transform on the echo signals in the distance dimension to obtain transformed echo signals), and performing mean cancellation on the multiple channel data after FFT to eliminate clutter introduced by stationary targets in a scene (i.e., performing clutter processing on the transformed echo signals to obtain preprocessed echo signals), and then performing coherent accumulation, where the accumulated data is distributed in the distance dimension and doppler dimension (i.e., performing coherent accumulation processing on the preprocessed echo signals in the channel dimension to obtain processing results); taking out the signal intensity S in the concerned distance range [ a, b ] (namely processing the processing result in the distance dimension in the preset distance range to obtain the second signal intensity of the echo signal in the preset distance range), obtaining the signal intensity mean value N in the whole range of the range, obtaining the ratio SNR of the signal in the concerned distance range to the signal intensity mean value in the whole detection area range in each Doppler unit, and calculating the mean value of the SNR in the concerned distance range (namely processing the processing result in the distance dimension in the preset distance range to obtain the second signal intensity of the echo signal in the preset distance range); finally, judging whether a living body moving target exists in the concerned distance range [ a, b ] or not by comparing the SNR with a set threshold (namely, detecting whether the target signal-to-noise ratio is larger than a preset signal-to-noise ratio or not to obtain a detection result, and determining whether the target object exists in the preset distance range or not according to the detection result. The specific treatment scheme can be as follows:
Step one: distance dimension FFT. The ADC data can be considered as a data matrix distributed in three dimensions of distance, speed and channel, and the ADC data of the ith frame can be expressed as X1 i (R N ,V N ,C N ) Wherein R is N Representing the number of sample points for a single chirp in the distance dimension, V N Representing that the single frame data contains chirp number, C N Representing the number of virtual channels. The ADC original data contains the distance information of the target, the FFT processing is carried out on the ADC original data in the distance dimension, the obtained frequency spectrum is positively correlated with the distance, the frequency can be converted into the target distance according to the relation between the frequency spectrum and the distance, the distribution condition of the target on the range profile can be obtained, and the data after 1DFFT is recorded as X2 i (R r ,V N ,C N ) Wherein R is r ≥R N 。
Further, X2 i In order to reduce side lobes of an amplitude curve in the FFT, the ADC data may optionally be windowed in the distance dimension (i.e. the echo signal is windowed in the distance dimension to obtain a windowed echo signal) before the distance dimension is FFT.
Fig. 4 is a schematic diagram of a transformed echo signal according to a second embodiment of the present invention, as shown in fig. 4, which is a 1DFFT spectrum of a living object existing in a scene, it can be seen that strong reflectors in the scene are mainly distributed between 0.5 and 2 m.
Fig. 5 is a schematic diagram of another transformed echo signal according to the second embodiment of the present invention, and as shown in fig. 5, is a 1DFFT spectrum of a living object in a scene.
Step two: stationary clutter removal. Obtaining 1DFFT data X2 in step one i (R r ,V N ,C N ) Thereafter, a mean cancellation operation may be utilized to remove the fieldTarget clutter is fixed in the scene. Specific operations may be, for example, 1DFFT data X2 of the ith frame i (R r ,V N ,C N ) Calculating the mean value of each distance unit in the speed dimension, such as n (1. Ltoreq.k. Ltoreq.C N ) K (k is more than or equal to 1 and less than or equal to R) of each channel r ) Average value m of each distance unit in speed dimension i The (k, n) calculation method may be as follows:
the result after average value cancellation is recorded as X3 i (R r ,V N ,C N ) The cancellation result corresponding to the kth chirp and the nth channel of the kth distance unit can be expressed as follows:
X3 i (k,q,n)＝X2 i (k,q,n)-m i (k,n)。
in order to eliminate stationary clutter in a scene, the mean cancellation operation can be performed on the transformed echo signals, and the effect of removing stationary clutter in the scene can be achieved through the mean cancellation operation shown in fig. 6 and fig. 7.
FIG. 6 is a schematic diagram of a preprocessed echo signal according to a second embodiment of the present invention, as shown in FIG. 6, the preprocessed echo signal generated in FIG. 4 is clutter processed; fig. 7 is a schematic diagram of another preprocessed echo signal according to the second embodiment of the present invention, and as shown in fig. 7, the preprocessed echo signal generated in fig. 5 is clutter-processed.
Step three: and (5) coherent accumulation. Obtaining a data matrix X3 after mean value cancellation in the second step i (R r ,V N ,C N ) Then, the data can be accumulated in the dimension of the virtual channel, namely, the data in the same distance unit and speed unit is subjected to C N Accumulation of individual channels, the coherently accumulated data is denoted as X4 i (R r ,V N ). The specific operation is as follows:
wherein k represents a kth distance unit, q represents a qth speed unit, X4 i (k, q) represents the result of coherent accumulation of the kth distance unit, the qth speed unit.
Step four: the signal and noise are calculated.
In step three, a coherent accumulation result X4 is obtained i (R r ,V N ) Assuming that the range of the interest is R1 to R2 and the range resolution unit of the radar is Δr, the range unit index where the corresponding interest distance is located is R1 to R2, and the calculation of R1 and R2 is as follows:
obtaining the concerned distance unit range [ r1, r2 ] by taking integer part of the calculation result]Calculating the average value X5 of all distance unit signal amplitudes under each speed dimension i (1,V N ) At the same time, the range of the distance unit of interest [ r1, r2 ] in each speed dimension is calculated]Mean value X6 of signal amplitude i (1,V N ) The calculation method can be as follows:
in the above expression abs (…) represents an absolute value of a number in parentheses, and if the number in the parentheses is a complex number, the corresponding amplitude value is represented.
Step five: and (5) obtaining a signal-to-noise ratio and a result judgment. Obtaining the signal-to-noise ratio X7 in the distance range according to the obtained result i The method comprises the following steps:
after X7 is obtained i After that, the following decision can be made:
if X7 i >1, then indicates that the i-th frame time is at distance [ R1, R2 ]]Within the range, a living moving object exists; if X7 i Less than or equal to 1, then the i-th frame moment is at the distance R1, R2]Within the range, the living body moving object does not exist.
Illustratively, in order to detect whether the distance region [0.8,1.1] (unit m) of interest has a target object, signal-to-noise ratio such as fig. 8 and 9 can be obtained by calculating the signal intensity average value of the region [0.8,1.1] and the signal intensity average value of the entire detection region and making the ratio.
Fig. 8 is a schematic diagram of a target snr according to a second embodiment of the present invention, as shown in fig. 8, which is the snr of each frame of a radar where a target object exists in a scene, it can be seen that the snr in the figure is greater than 1.
Fig. 9 is a schematic diagram of another target snr according to the second embodiment of the present invention, as shown in fig. 9, which is the snr of each frame of the radar where no target object exists in the scene, it can be seen that the snr of each frame of the radar in the scene without target is less than or equal to 1.
Therefore, whether the target object at the specified distance exists in the scene can be judged.
It can be found that the current living body detection algorithm based on millimeter wave radar generally has the problems of large calculated amount and poor real-time performance, needs to consume more hardware resources, and is difficult to quickly detect the real living body in the scene. Meanwhile, a large number of methods for detecting vital sign signals in a fixed scene exist at present, false targets introduced by complex vehicle cabin environments and life body movement diversity cannot be effectively removed, and the problems of high false alarm rate and high false alarm rate are generally solved.
In addition, the in-cabin living body detection method based on vision is easy to violate the privacy of passengers in a vehicle, and is undetectable for a target in a camera blind area.
The detection method provided by the embodiment of the invention can judge whether the moving object of the living body exists or not from the single frame data result by using fewer signal processing steps, so that the moving living body in the scene can be detected rapidly and in high real time, the calculation force and the storage resource are saved, and the hardware cost is reduced. In addition, the embodiment of the invention has the obvious advantage of not invading privacy.
Example III
Fig. 10 is a schematic structural diagram of a detection device for a target object according to a third embodiment of the present invention. As shown in fig. 10, the apparatus includes:
An acquisition module 310, configured to acquire echo signals of the MIMO millimeter wave radar, where the echo signals are distributed in three dimensions of a distance, a speed, and a channel;
the signal processing module 320 is configured to perform signal processing on the echo signal to obtain a processing result, where the processing result corresponds to two dimensions of a distance and a speed;
the determining module 330 is configured to determine a target signal-to-noise ratio of the echo signal within a preset distance range based on the processing result, and detect whether a target object exists within the preset distance range of the vehicle according to the target signal-to-noise ratio.
According to the detection device for the target object, provided by the embodiment of the invention, echo signals of the MIMO millimeter wave radar are acquired through the acquisition module, and the echo signals are distributed in three dimensions of distance, speed and channel; performing signal processing on the echo signals through a signal processing module to obtain processing results, wherein the processing results correspond to two dimensions of distance and speed; and determining a target signal-to-noise ratio of the echo signal in a preset distance range based on the processing result by a determining module, and detecting whether a target object exists in the preset distance range of the vehicle according to the target signal-to-noise ratio. By using the device, the processing result is obtained by carrying out signal processing on the echo signal, the target signal-to-noise ratio of the echo signal in the preset distance range is determined based on the processing result, and whether the target object exists in the preset distance range of the vehicle or not is detected according to the target signal-to-noise ratio, so that the detection of the target object can be rapidly realized on the basis of simplifying the detection method, and the real-time performance of the detection is improved.
Optionally, the signal processing module 320 includes:
the preprocessing unit is used for preprocessing the echo signals to obtain preprocessed echo signals;
and the processing unit is used for carrying out coherent accumulation processing on the preprocessed echo signals in the channel dimension to obtain a processing result.
Optionally, the preprocessing unit includes:
the transformation subunit is used for carrying out Fourier transformation on the echo signals in the distance dimension to obtain transformed echo signals;
and the clutter processing subunit is used for carrying out clutter processing on the converted echo signals to obtain preprocessed echo signals.
Optionally, the preprocessing unit further includes:
the windowing processing subunit is used for carrying out windowing processing on the echo signal in the distance dimension before carrying out Fourier transformation on the echo signal in the distance dimension to obtain a transformed echo signal, so as to obtain a windowed echo signal;
the transformation subunit is specifically configured to:
and carrying out Fourier transform on the windowed echo signals in a distance dimension to obtain transformed echo signals.
Optionally, the clutter processing subunit is specifically configured to:
Calculating the average value of the transformed echo signals in the speed dimension;
and determining a preprocessed echo signal based on the transformed echo signal and the mean value.
Optionally, the determining module 330 includes:
a first determining unit, configured to determine a first signal strength of the echo signal within a complete distance range based on the processing result;
a second determining unit, configured to determine a second signal strength of the echo signal within a preset distance range based on the processing result;
and the calculating unit is used for calculating the target signal-to-noise ratio of the echo signal in a preset distance range according to the first signal intensity and the second signal intensity.
Optionally, the first determining unit is specifically configured to:
and processing the processing result in the distance dimension within the complete distance range to obtain the first signal intensity of the echo signal within the complete distance range.
Optionally, the second determining unit is specifically configured to:
and processing the processing result in the distance dimension within a preset distance range to obtain the second signal intensity of the echo signal within the preset distance range.
Optionally, the determining module 330 is specifically configured to:
Detecting whether the target signal-to-noise ratio is greater than a preset signal-to-noise ratio or not to obtain a detection result;
and determining whether the vehicle has a target object within a preset distance range or not based on the detection result.
The target object detection device provided by the embodiment of the invention can execute the target object detection method provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.
Example IV
Fig. 11 is a schematic structural view of a vehicle according to a fourth embodiment of the present invention. Vehicles are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. Vehicles may also represent various forms of mobile devices, such as personal digital assistants, cellular telephones, smart phones, wearable devices (e.g., helmets, eyeglasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.
As shown in fig. 11, the vehicle 10 includes at least one processor 11, and a memory, such as a Read Only Memory (ROM) 12, a Random Access Memory (RAM) 13, etc., communicatively connected to the at least one processor 11, in which the memory stores a computer program executable by the at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the Read Only Memory (ROM) 12 or the computer program loaded from the storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the vehicle 10 may also be stored. The processor 11, the ROM 12 and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to bus 14.
Various components in the vehicle 10 are connected to the I/O interface 15, including: an input unit 16 such as a keyboard, a mouse, etc.; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, an optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the vehicle 10 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunications networks.
The processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, digital Signal Processors (DSPs), and any suitable processor, controller, microcontroller, etc. The processor 11 performs the respective methods and processes described above, for example, a target object detection method.
In some embodiments, the method of detecting a target object may be implemented as a computer program tangibly embodied on a computer-readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the vehicle 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the above-described target object detection method may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the method of detection of the target object in any other suitable way (e.g. by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.
A computer program for carrying out methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be implemented. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on a vehicle having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and pointing device (e.g., a mouse or a trackball) by which a user can provide input to the vehicle. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), blockchain networks, and the internet.
The computing system may include clients and servers. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical hosts and VPS service are overcome.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present invention may be performed in parallel, sequentially, or in a different order, so long as the desired results of the technical solution of the present invention are achieved, and the present invention is not limited herein.
The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.
Claims (12)
1. A method of detecting a target object, the method being applied to a vehicle on which a MIMO millimeter wave radar is mounted, the method comprising:
acquiring echo signals of the MIMO millimeter wave radar, wherein the echo signals are distributed in three dimensions of distance, speed and channel;
performing signal processing on the echo signals to obtain processing results, wherein the processing results correspond to two dimensions of distance and speed;
And determining a target signal-to-noise ratio of the echo signal in a preset distance range based on the processing result, and detecting whether a target object exists in the preset distance range of the vehicle according to the target signal-to-noise ratio.
2. The method of claim 1, wherein the performing signal processing on the echo signal to obtain a processing result includes:
preprocessing the echo signals to obtain preprocessed echo signals;
and carrying out coherent accumulation processing on the preprocessed echo signals in the channel dimension to obtain processing results.
3. The method of claim 2, wherein the preprocessing the echo signal to obtain a preprocessed echo signal comprises:
performing Fourier transform on the echo signals in a distance dimension to obtain transformed echo signals;
and performing clutter processing on the transformed echo signals to obtain preprocessed echo signals.
4. A method according to claim 3, further comprising, prior to said fourier transforming said echo signals in the distance dimension, the step of:
windowing the echo signal in a distance dimension to obtain a windowed echo signal;
Performing fourier transform on the echo signal in a distance dimension to obtain a transformed echo signal, including:
and carrying out Fourier transform on the windowed echo signals in a distance dimension to obtain transformed echo signals.
5. The method of claim 3, wherein said clutter processing said transformed echo signals to obtain preprocessed echo signals comprises:
calculating the average value of the transformed echo signals in the speed dimension;
and determining a preprocessed echo signal based on the transformed echo signal and the mean value.
6. The method of claim 1, wherein determining a target signal-to-noise ratio of the echo signal within a preset distance range based on the processing result comprises:
determining a first signal strength of the echo signal within a complete distance range based on the processing result;
determining a second signal intensity of the echo signal in a preset distance range based on the processing result;
and calculating the target signal-to-noise ratio of the echo signal in a preset distance range according to the first signal intensity and the second signal intensity.
7. The method of claim 6, wherein determining a first signal strength of the echo signal over a full range of distances based on the processing result comprises:
and processing the processing result in the distance dimension within the complete distance range to obtain the first signal intensity of the echo signal within the complete distance range.
8. The method of claim 6, wherein determining a second signal strength of the echo signal within a preset distance range based on the processing result comprises:
and processing the processing result in the distance dimension within a preset distance range to obtain the second signal intensity of the echo signal within the preset distance range.
9. The method of claim 1, wherein the detecting whether a target object is present within a preset distance range of the vehicle based on the target signal-to-noise ratio comprises:
detecting whether the target signal-to-noise ratio is greater than a preset signal-to-noise ratio or not to obtain a detection result;
and determining whether the vehicle has a target object within a preset distance range or not based on the detection result.
10. A target object detection device, the device being configured in a vehicle, comprising:
The acquisition module is used for acquiring echo signals of the MIMO millimeter wave radar, wherein the echo signals are distributed in three dimensions of distance, speed and channel;
the signal processing module is used for performing signal processing on the echo signals to obtain processing results, and the processing results correspond to the two dimensions of the distance and the speed;
and the determining module is used for determining the target signal-to-noise ratio of the echo signal in the preset distance range based on the processing result and detecting whether a target object exists in the preset distance range of the vehicle according to the target signal-to-noise ratio.
11. A vehicle, characterized in that the vehicle comprises:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the method of detecting a target object according to any one of claims 1-9.
12. A computer readable storage medium storing computer instructions for causing a processor to perform the method of detecting a target object according to any one of claims 1-9.
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