New architecture distributed mimo radar system, method of detecting and medium

Abstract

This invention discloses a novel distributed MIMO radar system, its detection method, and a medium. The system includes: at least two distributed transmitting platforms, each including at least two transmitting antennas; at least two distributed receiving platforms, each including at least two receiving antennas; and a control and analysis processing device configured to: transmit radar transmitted wave signals with mutually orthogonal waveforms through each transmitting antenna of each transmitting platform; and receive received signals reflected from a target by the radar transmitted wave signals through each receiving antenna of each receiving platform; perform down-conversion sampling and matched filtering on the received signals to generate a transmit-receive-pulse vector of the received signals; and detect the target based on the transmit-receive-pulse vector of the received signals using an incoherent detector, a coherent detector, an approximately coherent detector, or a hybrid detector.

Description

Technical Field

[0001] This invention relates to the field of radar technology, and in particular to a novel distributed multiple-input multiple-output (MIMO) radar system and its detection method and medium. Background Technology

[0002] Radar is a crucial component of modern defense systems and advanced weapon systems, undertaking primary tasks such as early warning, surveillance, intelligence gathering, and precision guidance. Radar can achieve long-range detection, tracking, and parameter estimation, and can even further realize imaging, target classification and identification, and tracking. Unlike other sensors such as cameras and ultrasonic sensors, radar's transmitted and echo signals are less affected by environmental interference, making it suitable for a wider range of scenarios and offering advantages such as all-weather, all-day operation and long detection range.

[0003] Target detection is one of the most basic and important applications of radar. Target detection is based on the characteristics of a target, such as its electromagnetic waves, acoustic and optical scattering. Radar target detection involves analyzing and identifying radar waves to determine whether a target exists within the detection area, and it is also a prerequisite for target tracking.

[0004] Currently, compared to monostatic radar, distributed MIMO radar mainly transmits different waveforms through multiple antennas, simultaneously covering a larger airspace, and utilizes long-term coherent accumulation to achieve a higher signal-to-noise ratio, effectively improving target detection, parameter estimation, and target tracking performance. However, traditional distributed MIMO radar systems typically use mechanically scanned antennas at each node, which cannot fully leverage the advantages of spatial diversity and waveform diversity at each node. Summary of the Invention

[0005] In view of this, embodiments of the present invention aim to provide a novel distributed MIMO radar system and its detection method and medium, which can improve the accuracy and reliability of target detection.

[0006] The technical solution of this invention is implemented as follows:

[0007] In a first aspect, embodiments of the present invention provide a novel distributed multiple-input multiple-output (MIMO) radar system, the system comprising:

[0008] The system consists of at least two distributed transmission platforms, each of which includes at least two transmission antennas.

[0009] The system comprises at least two receiving platforms in a distributed configuration, each receiving platform including at least two receiving antennas; in each transmitting or receiving platform, the distance between adjacent transmitting antennas or the distance between adjacent receiving antennas is half the wavelength of the radar wave emitted by the transmitting antenna.

[0010] The control and analysis processing equipment is configured to: transmit radar transmitted wave signals with mutually orthogonal waveforms through each transmitting antenna of each transmitting platform, and receive the received signal reflected by the radar transmitted wave signal from the detected target through each receiving antenna of each receiving platform.

[0011] Furthermore, the received signal is down-converted, sampled, and matched-filtered to generate the transmit-receive-pulse vector of the received signal;

[0012] Based on the transmit-receive-pulse vector of the received signal, the target to be detected is detected by an incoherent detector, a coherent detector, an approximately coherent detector, or a hybrid detector.

[0013] Secondly, embodiments of the present invention provide a target detection method for a novel distributed MIMO radar system, the method comprising:

[0014] The radar transmit wave signals with mutually orthogonal waveforms are transmitted through each transmit antenna of each transmit platform, and the received signal reflected by the radar transmit wave signal after being detected is received through each receive antenna of each receive platform.

[0015] Furthermore, the received signal is down-converted, sampled, and matched-filtered to generate the transmit-receive-pulse vector of the received signal;

[0016] Based on the transmit-receive-pulse vector of the received signal, the target to be detected is detected by an incoherent detector, a coherent detector, an approximately coherent detector, or a hybrid detector.

[0017] Thirdly, embodiments of the present invention provide a computer storage medium storing at least one instruction, which is executed by a processor to implement the functions of each component in the novel distributed MIMO radar system as described in the first aspect or the target detection method of the novel distributed MIMO radar as described in the second aspect.

[0018] This invention provides a novel distributed MIMO radar system, its detection method, and medium. By distributing the transmission and receiving platforms, and configuring each transmission and receiving platform as a centralized MIMO radar structure consisting of multiple transmitting antennas and multiple receiving antennas, the advantages of both distributed and centralized MIMO radars are combined, thereby improving the target detection accuracy. Attached Figure Description

[0019] Figure 1 A schematic diagram of a novel distributed MIMO radar system provided in an embodiment of the present invention;

[0020] Figure 2 A schematic diagram illustrating a novel distributed MIMO radar system provided in this embodiment of the invention;

[0021] Figure 3 An angle diagram provided for an embodiment of the present invention;

[0022] Figure 4 The relationship between the detection probability of an incoherent detector and the signal-to-noise ratio difference under the condition of non-fluctuating targets;

[0023] Figure 5 A schematic diagram illustrating the relationship between the detection probability of incoherent detectors and the difference in signal-to-noise ratio for Swerling 0 and Swerling I targets;

[0024] Figure 6 The relationship between the detection probability of an incoherent detector and the signal-to-noise ratio under non-fluctuating target conditions with different pulse numbers;

[0025] Figure 7 This diagram illustrates the relationship between the detection probability of the incoherent detector and the signal-to-noise ratio for targets with different pulse numbers (Swerling 0 and Swerling I).

[0026] Figure 8 A schematic diagram illustrating the relationship between the detection probability of the incoherent detector and the signal-to-noise ratio for targets with different numbers of array elements (P). m =1, Q n The case where =1 is the case of traditional distributed MIMO radar;

[0027] Figure 9 A schematic diagram showing the relationship between the detection probability of the incoherent detector and the difference in signal-to-noise ratio when the product of the number of array elements is 12, for targets with Swerling 0 and Swerling I.

[0028] Figure 10 The relationship between the detection probability of an approximately coherent detector and the difference in signal-to-noise ratio under the condition of non-fluctuating targets;

[0029] Figure 11 A schematic diagram illustrating the relationship between the detection probability of an approximately coherent detector and the difference in signal-to-noise ratio for Swerling 0 and Swerling I targets;

[0030] Figure 12This is a schematic diagram showing the relationship between the detection probability of an approximately coherent detector and the signal-to-noise ratio when the number of pulses is different for a non-fluctuating target.

[0031] Figure 13 This is a schematic diagram showing the relationship between the detection probability of the approximate coherent detector and the signal-to-noise ratio for targets with different pulse numbers (Swerling 0 and Swerling I).

[0032] Figure 14 A schematic diagram illustrating the relationship between the detection probability and signal-to-noise ratio difference of the approximate coherent detector for targets with different numbers of array elements (P). m =1, Q n The case where =1 is the case of traditional distributed MIMO radar;

[0033] Figure 15 A schematic diagram illustrating the relationship between the detection probability of a coherent detector and the difference in signal-to-noise ratio when the target is non-undulating;

[0034] Figure 16 A schematic diagram showing the relationship between the detection probability of a coherent detector and the difference in signal-to-noise ratio for Swerling 0 and Swerling I targets;

[0035] Figure 17 This is a schematic diagram showing the relationship between the detection probability of a coherent detector and the signal-to-noise ratio when the number of pulses is different for a non-fluctuating target.

[0036] Figure 18 This diagram illustrates the relationship between the detection probability of a coherent detector and the signal-to-noise ratio for targets with different pulse numbers (Swerling 0 and Swerling I).

[0037] Figure 19 A schematic diagram illustrating the relationship between the detection probability and signal-to-noise ratio of coherent detectors for targets with different numbers of array elements (P). m =1, Q n The case where =1 is the case of traditional distributed MIMO radar;

[0038] Figure 20 A schematic diagram showing the relationship between the detection probability and the signal-to-noise ratio of the approximate coherent detector and the coherent detector when K=12;

[0039] Figure 21 This diagram illustrates the relationship between the detection probability of the hybrid detector and the signal-to-noise ratio in the case of non-undulating targets.

[0040] Figure 22 A schematic diagram illustrating the relationship between the detection probability of the hybrid detector and the signal-to-noise ratio when the target is Swerling 0 or Swerling I.

[0041] Figure 23 This diagram illustrates the relationship between the detection probability and signal-to-noise ratio of the hybrid detector for targets with different pulse numbers (Swerling 0 and Swerling I).

[0042] Figure 24 A schematic diagram illustrating the relationship between the detection probability and signal-to-noise ratio of the hybrid detector for targets with different numbers of array elements (P). m =1, Q n The case where =1 is the case of traditional distributed MIMO radar;

[0043] Figure 25 A schematic diagram illustrating the relationship between the detection probability and signal-to-noise ratio of four detectors when the target is non-undulating;

[0044] Figure 26 A schematic diagram illustrating the relationship between the detection probability and signal-to-noise ratio differences of four detectors when dealing with fluctuating targets.

[0045] Figure 27 This is a schematic diagram of a target detection method for a novel distributed MIMO radar system provided in an embodiment of the present invention. Detailed Implementation

[0046] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0047] To improve the target detection performance of traditional distributed MIMO radar systems, see [link / reference]. Figure 1 This illustrates a novel distributed MIMO radar system 1 provided by an embodiment of the present invention. System 1 may include:

[0048] At least two launch platforms Tx1, Tx2, ..., Tx are configured in a distributed manner. M Each launch platform includes at least two launch antennas;

[0049] In this embodiment of the invention, combined with Figure 1 The m-th launch platform Tx m Including P m There are 1 transmitting antenna, each labeled T. m,0 T m,1 ,…,T m,Pm-1 ;

[0050] A distributed setup requires at least two receiving platforms, Rx1, Rx2, ..., Rx N Each receiving platform includes at least two receiving antennas;

[0051] In this embodiment of the invention, combined with Figure 1 The nth receiving platform R xn Including Q n There are 1 receiving antenna, each labeled R. n,0 R n,1 , ..., R n,Qn-1 ;

[0052] For each transmitting or receiving platform, the distance d between adjacent transmitting antennas or the distance d between adjacent receiving antennas is... T It is half the wavelength of the radar wave emitted by the transmitting antenna;

[0053] The control and analysis processing device 10 is configured to: transmit radar transmitted wave signals with mutually orthogonal waveforms through each transmitting antenna of each transmitting platform, and receive the received signal reflected by the radar transmitted wave signal from the detected target through each receiving antenna of each receiving platform.

[0054] Furthermore, the received signal is down-converted, sampled, and matched-filtered to generate the transmit-receive-pulse vector of the received signal;

[0055] Based on the transmit-receive-pulse vector of the received signal, the target to be detected is detected by an incoherent detector, a coherent detector, an approximately coherent detector, or a hybrid detector.

[0056] In this embodiment of the invention, the control and analysis processing device 10 can be specifically implemented as a computing device, such as at least one of a smartphone, smartwatch, desktop computer, laptop, virtual reality terminal, augmented reality terminal, wireless terminal, and laptop computer. This computing device has communication capabilities and can access wired or wireless networks. The computing device can refer to one of multiple terminals; those skilled in the art will understand that the number of terminals can be more or less. In some examples, the computing device can perform the functions of the control and analysis processing device 10. It is understood that the computing device undertakes the calculation and processing work of the technical solution of this invention, and this embodiment of the invention does not limit this aspect.

[0057] The above technical solution combines the advantages of distributed MIMO radar and centralized MIMO radar by setting up a distributed transmission platform and a receiving platform, with each platform configured as a centralized MIMO radar structure consisting of multiple transmitting antennas and multiple receiving antennas, thereby improving the target detection accuracy.

[0058] for Figure 1 In the technical solution shown, in some possible implementations, the detection area formed by each transmitting platform and each receiving platform is an elliptical region, with the foci of the ellipse being the transmitting platform and the receiving platform that form the detection area, respectively.

[0059] Specifically, regarding the above implementation method, we will take two transmitting platforms and two receiving platforms as examples, as follows: Figure 2 As shown, the transmitting platforms Tx1 and Tx2 form four elliptical detection areas with the receiving platforms Rx1 and Rx2, respectively. This allows each receiving platform to collect the echo signals transmitted by all transmitting platforms, fully combining the advantages of distributed MIMO radar and centralized MIMO radar, thereby improving the detection accuracy of the target.

[0060] for Figure 1 In some possible implementations of the technical solution shown, the control and analysis processing device 10 is configured as follows:

[0061] The radar transmit signal is transmitted through the p-th transmitting antenna of the m-th transmitting platform. Among them, s m,p (t) represents the complex baseband waveform, f c Indicates the carrier frequency;

[0062] The target echo signal is received by the q-th receiving antenna of the n-th receiving platform from all the transmitting antennas of the m-th transmitting platform. Among them, P m This represents the total number of transmitting antennas on the m-th transmitting platform; f′=f c +f d,m,n (θ m,n ,v),f d,m,n (θ m,n ,v) represents the Doppler frequency shift caused by the relative motion of the detected target with respect to the m-th transmitting platform and the n-th receiving platform; t′=t-τ (m,p)(n,q) (θ m,n )-kT p , τ (m,p)(n,q) (θ m,n θ represents the time delay from the p-th transmitting antenna of the m-th transmitting platform to the q-th receiving antenna of the n-th receiving platform. m,n This represents the angle between the line connecting the center of the elliptical detection region formed by the m-th transmitting platform and the n-th receiving platform and the major axis of the elliptical detection region, such as... Figure 3 As shown, k represents the pulse number, T p Indicates the pulse repetition period; a m,n This represents the scattering coefficient of the target being detected;

[0063] The received signals through each receiving antenna of each receiving platform include the target echo signal and the interference signal.

[0064] The above implementation method describes, for example Figure 1The signal model of the novel distributed MIMO radar system 1 is shown. Specifically, for the above implementation, the Doppler frequency shift f caused by the relative motion of the detected target with respect to the m-th transmitting platform and the n-th receiving platform... d,m,n (θ m,n v) is shown in the following formula:

[0065]

[0066] In the above formula, These represent the directions from the m-th transmitting platform and the n-th receiving platform to the detected target, respectively. This represents the definition symbol, where p is the position of the target being detected. T,m and p R,n Let p and p represent the positions of the m-th transmitting platform and the n-th receiving platform, respectively. Since the number of detected targets may be greater than 1, p and p T,m and p R,n Both are vectors.

[0067] The time delay τ from the p-th transmitting antenna of the m-th transmitting platform to the q-th receiving antenna of the n-th receiving platform (m,p)(n,q) (θ m,n It can be represented by the following formula:

[0068]

[0069] Among them, such as Figure 3 As shown, θ T,m θ is the visible view from the m-th launch platform to the target. R,n It is the viewpoint from the nth receiving platform to the target.

[0070] Understandably, the above implementation method and its specific examples indicate that, on a distributed platform, the transmitting and receiving antennas are still deployed according to the centralized MIMO radar configuration, thereby providing a mathematical model basis for the radar system described in the embodiments of the present invention to combine the advantages of distributed MIMO radar and centralized MIMO radar in the target detection process.

[0071] Based on the above implementation method, in some examples, the control and analysis processing device 10 is configured as follows:

[0072] By sampling the complex baseband waveform in the radar transmitted signal and performing down-conversion processing on the target signal, the target echo signal of the k-th pulse signal is obtained as follows:

[0073]

[0074] in, This represents the signal matrix of the m-th transmitting platform, where L represents the length of the transmitted signal; a m (θ m,n ) represents the launch steering vector, b h (θ m,n ) represents the receiving guide vector, a m,p (θ m,n ) and b n,q (θ m,n ) represent a respectively m (θ m,n ) and b n (θ m,n The p-th and q-th elements of ), a m (θ m,n ) and b n (θ m,n They can be represented as:

[0075]

[0076]

[0077] d T The wavelength of the emitted waveform is represented by Q, where c represents the speed of light. n θ represents the total number of receiving antennas on the nth receiving platform. T,m θ represents the visible field of view from the m-th launching platform to the detected target. R,n The visible view from the nth receiving platform to the detected target is represented by: The Doppler vectors of the mth transmitting platform and the nth receiving platform during the kth pulse are represented as:

[0078]

[0079] By using the sampled signal of the complex baseband waveform in the radar transmitted wave signal to perform matched filtering on the target echo signal of the k-th pulse signal, the transmit-receive-pulse vector of the target echo signal is obtained as follows:

[0080]

[0081] in, S represents the Kronecker product. f α represents the Doppler signal portion of the target echo signal. mn This represents the amplitude signal portion of the target echo signal;

[0082] Based on the target echo signal's transmit-receive pulse vector x m,n and interference signal n m,n The received signal is obtained as: y m,n =x m,n +n m,n .

[0083] In the example above, specifically, the Doppler vector d of the m-th transmitting platform and the n-th receiving platform during the k-th pulse. k (f d,m,n (θ m,n ,υ)) can also be referred to in some implementations as the steering vector of the m-th transmitting platform and the n-th receiving platform in the pulse (slow time) dimension.

[0084] Furthermore, since the transmitted waveforms of each transmitting antenna on each transmitting platform are assumed to be orthogonal to each other, such as orthogonal linear frequency modulated signals, then the transmit-receive-pulse vector of the target echo signal can be obtained by performing matched filtering on the transmitted signal. This vector is only used to represent one form of the target echo signal, to facilitate the subsequent description of the target detection method. Additionally, in this embodiment of the invention, n can be set... m,n It follows a Gaussian distribution.

[0085] Based on the above implementation methods, examples, and detailed descriptions, a mathematical model for target detection is provided for the novel distributed MIMO radar system 1 provided in this embodiment of the invention. Based on this mathematical model, this embodiment of the invention provides four methods for detecting the target: incoherent detector, coherent detector, approximately coherent detector, and hybrid detector. The performance of these detection methods is analyzed by combining the false alarm probability and the target detection probability.

[0086] In some examples, for detection using an incoherent detector, the control and analysis processing device 10 is configured as follows:

[0087] Based on the binary detection principle and the received signal, two hypothetical scenarios are constructed: the first hypothetical scenario is described as the received signal not including the target echo signal but only including the interference signal, and the second hypothetical scenario is described as the received signal including both the target echo signal and the interference signal, with the amplitude signal portion and the Doppler signal portion in the received signal treated as a whole.

[0088] Based on the received signals from all receiving platforms, the first likelihood function and the second likelihood function corresponding to the first assumption and the second assumption respectively are obtained;

[0089] The incoherent detector is obtained based on the first likelihood function and the second likelihood function;

[0090] Based on the fact that incoherent detectors do not contain signal-to-noise ratio weighting coefficients, a first statistic for incoherent detection is obtained;

[0091] The first statistic is compared with a set incoherent detector threshold. When the first statistic is greater than the threshold, it is determined that the detected target exists.

[0092] In this example, it's important to note that the binary detection principle requires making separate assumptions about whether the target exists or not. These assumptions determine the final conclusion, which must be chosen from two possible outcomes, resulting in a binary conclusion. To determine a specific distance, Doppler signal, or angular signal, a detection process must be performed; this procedure is called binary detection. The entire detection process is repeated MN times, resulting in an MN-ary decision. To improve reliability, it's required that the target is detected M0N0 times out of the MN decisions to ultimately confirm the existence of a valid target; this process is called binary accumulation.

[0093] Furthermore, incoherent detection does not rely on precise real-time channel information to detect signals, and the receiving equipment is relatively simple. Incoherent accumulation removes phase information and instead accumulates the amplitude or squared amplitude of the sampled data. The incoherent detection of the novel distributed MIMO radar system provided in this embodiment of the invention actually performs incoherent accumulation both within and between stations. In the above example, the incoherent detector is an energy detector; when the detection statistic is greater than a threshold, a target is considered to be present within the detection range, and vice versa. Since the incoherent detector does not rely on precise real-time phase information, the amplitude signal and the Doppler signal can be considered as a whole, and the received signal can be represented as x. m,n =α m,n s f =β m,n , where β m,n =α m,n s f .

[0094] Based on this, the object detection problem can be described by the following assumptions:

[0095] H0:y m,n =n m,n

[0096] H1:y m,n =β m,n +n m,n

[0097] In other words, the first assumption is H0, and the second assumption is H1.

[0098] definition Including all received signals, the likelihood functions under H0 and H1 can be expressed as follows:

[0099]

[0100]

[0101] Where, δ 2 Indicates the power (variance) of the interference signal;

[0102] By taking the logarithm of the likelihood function above, the incoherent detector can be expressed as:

[0103]

[0104] In the incoherent case, β m,n The maximum likelihood estimate of y m,n .

[0105] Since incoherent detectors do not contain signal-to-noise ratio weighting coefficients, the contribution of each spatial diversity channel is assumed to be equal. Therefore, the incoherent detection statistic can be defined as:

[0106]

[0107] For the aforementioned incoherent detection statistics, by using T NCD With the set incoherent detector threshold γ NCD The comparison is performed to determine whether the target exists, i.e. whether the target has been detected.

[0108] For the false alarm probability P of an incoherent detector f The sum of the object detection probability P d In this example, T NCD It involves 2L The sum of squares of independent and identically distributed Gaussian random variables, with variance δ. 2 / 2, and it has a zero mean in case H0 and a non-zero mean in case H1, therefore:

[0109]

[0110] In the above formula, It is a central chi-square distribution with 2L degrees of freedom. The distribution is a non-central chi-square distribution with 2L degrees of freedom, and the non-central parameter λ. NCD for

[0111] Based on the above, the false alarm probability P of incoherent detection f The sum of the object detection probability P d for:

[0112]

[0113]

[0114] Where, γ NCD For incoherent detector threshold, Let Γ(·) be the incomplete gamma function, and Q be the gamma function. m (a,b) is the generalized Marcum Q function.

[0115] In some examples, for detection using a coherent detector, the control and analysis processing device 10 is configured as follows:

[0116] Based on the binary detection principle and the received signal, two hypothetical scenarios are constructed: the first hypothetical scenario is described as the received signal not including the target echo signal but only including the interference signal, and the second hypothetical scenario is described as the received signal including both the target echo signal and the interference signal, with the amplitude signal part and the phase signal part of the received signal being separated.

[0117] Based on the received signals from all receiving platforms, the third likelihood function and the fourth likelihood function corresponding to the first assumption and the second assumption respectively are obtained;

[0118] The coherent detector is obtained based on the third and fourth likelihood functions;

[0119] A second statistic for coherent detection is obtained based on the coherent detector;

[0120] The second statistic is compared with a set coherent detector threshold. When the second statistic is greater than the threshold, it is determined that the detected target exists.

[0121] In this example, it should be noted that the coherent detector needs to compensate for both the signal amplitude and phase. Therefore, the amplitude signal and phase signal need to be separated. To reflect the difference in target strength across different transmit and receive paths, in practice, the common part α can be used... 1,1 It is proposed that β m,n This represents the signal-to-noise ratio difference between each transmitter and receiver, which is then compensated separately. Therefore, the received signal can be modeled as follows:

[0122]

[0123] in,

[0124] Based on this, the object detection problem can be described by the following assumptions:

[0125] H0:y m,n =n m,n

[0126] H1:ym,n =β m,n +n m,n

[0127] In other words, the first assumption is H0, and the second assumption is H1.

[0128] The third and fourth likelihood functions under H0 and H1 can be expressed as follows:

[0129]

[0130]

[0131] By taking the logarithm of the likelihood function above, the coherent detector can be expressed as:

[0132]

[0133] Relating the above equation to α 1,1 Taking the derivative and setting it to 0, we get:

[0134]

[0135] Right now:

[0136]

[0137] Therefore, we can obtain Substituting it into L(Y) yields:

[0138]

[0139] Discarding irrelevant terms and simplifying the above equation, we obtain the detection statistic for the coherent detector as follows:

[0140]

[0141] For the above coherent detection statistics, by using T CD With the set coherent detector threshold γ CD A comparison is made, and the existence of the target to be detected is determined based on the comparison result, that is, whether the target to be detected has been detected.

[0142] For the false alarm probability P of the coherent detector f And the target detection probability P d In this example, the definition is... Then the coherent detector can be written as T CD =|Y| 2 If Y follows a complex Gaussian distribution, then E{Y / H0}=0. Where E represents the expectation operation and D represents the variance operation.

[0143] definition but It follows the chi-square distribution as follows:

[0144] Among them, non-central parameters

[0145] Based on the above distribution, the false alarm probability P of the coherent detector f And the target detection probability P d They are respectively:

[0146]

[0147]

[0148] Based on the above examples, in some examples, the control and analysis processing device 10 is configured as follows:

[0149] Based on the second statistic used for coherent detection, a third statistic is obtained by reducing the amplitude information to perform near-coherent detection;

[0150] The third statistic is compared with a set threshold for an approximate coherent detector. When the third statistic is greater than the threshold for an approximate coherent detector, it is determined that the detected target exists.

[0151] It should be noted that coherent processing in both the spatial and Doppler domains offers higher resolution and performance gains in target detection and estimation compared to incoherent processing, but it requires additional phase synchronization between all sensors. However, an approximately coherent detector only requires knowledge of the initial phase φ of all receivers and transmitters. m,n Paired TX-RX delay τ m,n and Doppler frequency f m,n Accurate estimation. Compared to coherent detectors, it reduces reliance on amplitude information and lowers system requirements. Based on this, θ is defined. m,n,k =φ m,n -2πf c τ m,n +2πf m,m Approximate coherent detectors only compensate for the phase of the target signal. Based on this, the statistics of an approximate coherent detector can be constructed from the detection statistics of a coherent detector.

[0152]

[0153] This shows that, compared to coherent detectors, near-coherent detectors do not require prior knowledge of the signal-to-noise ratio differences of the target on different transmission and reception paths, making them easier to implement than coherent detectors.

[0154] For the false alarm probability P of an approximately coherent detectorf And the target detection probability P d In this example, the definition is... Then the approximate coherent detector can be written as T ACD =|X| 2 Then we have:

[0155]

[0156] In other words, the test statistic for approximately coherent detection follows a chi-square distribution:

[0157]

[0158] Among them, non-central parameters

[0159] Based on the above distribution, the false alarm probability P of coherent detection is... f And the target detection probability P d They are respectively:

[0160]

[0161]

[0162] Where, γ ACD This is the threshold for an approximate coherent detector.

[0163] In some examples, for detection using hybrid detectors, the control and analysis processing device 10 is configured as follows:

[0164] Based on the binary detection principle and the received signal, two hypothetical scenarios are constructed: the first hypothetical scenario is described as the received signal not including the target echo signal but only including the interference signal, and the second hypothetical scenario is described as the received signal including both the target echo signal and the interference signal.

[0165] Based on the received signals from all receiving platforms, the fifth likelihood function and the sixth likelihood function corresponding to the first assumption and the second assumption respectively are obtained;

[0166] The hybrid detector is obtained based on the fifth and sixth likelihood functions;

[0167] The signals from the hybrid detector are coherently accumulated within the same receiving platform and incoherently accumulated between different receiving platforms to obtain a fourth statistic for hybrid detection.

[0168] The fourth statistic is compared with a set hybrid detector threshold. When the fourth statistic is greater than the threshold, it is determined that the detected target exists.

[0169] In this example, it should be noted that the hybrid detector essentially performs coherent accumulation of the signal within the same receiving platform and incoherent accumulation between different receiving platforms. Therefore, the signal received by the hybrid detector can be represented as:

[0170] x m,n =α m,n s f

[0171] Based on this, the object detection problem can be described by the following assumptions:

[0172] H0:y m,n =n m,n

[0173] H1:y m,n =x m,n +n m,n

[0174] The fifth and sixth likelihood functions under H0 and H1 can be expressed as follows:

[0175]

[0176] By taking the logarithm of the likelihood function above, the hybrid detector can be expressed as:

[0177]

[0178] Ignore α mn Irrelevant terms can simplify the above equation to:

[0179]

[0180] Relating the above equation to α mn Taking the derivative and setting it to 0, we get:

[0181]

[0182] Right now:

[0183]

[0184] Therefore, we can obtain Will α m,n Substituting the simplified L(Y) into the equation, we get:

[0185]

[0186] Discarding irrelevant terms and simplifying the above equation, we obtain the detection statistic for the hybrid detector as follows:

[0187]

[0188] For the above mixed detection statistic, by using T HD With the set hybrid detector threshold γ HD A comparison is made, and the existence of the target to be detected is determined based on the comparison result, that is, whether the target to be detected has been detected.

[0189] For the false alarm probability P of the hybrid detector f And the target detection probability P d In this example, the definition is... in Let y be a complex Gaussian random variable. m,n A linear transformation of . Based on this definition, we can obtain

[0190] In case H1, Then we have:

[0191]

[0192]

[0193] We can obtain:

[0194]

[0195]

[0196] in, According to the summation rules for weighted central / non-central chi-square random variables, the raw detection statistic of the hybrid detector should follow the following distribution:

[0197]

[0198] in,

[0199] Based on the above distribution, the false alarm probability P of the hybrid detector is... f And the target detection probability P d They are respectively:

[0200]

[0201]

[0202] This invention provides an embodiment of the technical solution through simulation experiments to illustrate its effectiveness. In the simulation experiments, Monte Carlo simulation is used for experimental verification and analysis. The simulation parameters are set as shown in Table 1.

[0203]

[0204] Table 1

[0205] In addition to the simulation parameters shown in Table 1, the carrier frequency is 3 GHz, and the target models simulated are a non-fluctuating target, a Swerling 0 type target model, and a Swerling I type target model. Understandably, the parameters shown in Table 1 will be changed accordingly during the simulation process based on simulation requirements.

[0206] Figures 4 to 9 Simulation results for incoherent detectors are shown. Specifically, Figure 4 The relationship curve between the detection probability of the incoherent detector and the signal-to-noise ratio difference is given in the case of non-fluctuating target. According to the simulation scenario in this paper, there are two propagation paths from a certain transmitting platform to the receiving platform. The horizontal axis represents the signal-to-noise ratio difference between the two propagation paths. Figure 5 The diagram shows a comparison of detection probabilities in Monte Carlo simulations of incoherent detectors under two target models: Swerling type 0 and Swerling type I. Figure 6 The diagram shows a comparison of the detection probabilities of an incoherent detector in Monte Carlo simulation and theoretical expression for non-fluctuating targets with different numbers of pulses. Figure 7 The diagram shows a comparison of the detection probabilities of the incoherent detector in Monte Carlo simulations for targets Swerling 0 and Swerling I with different numbers of pulses. Figure 8 The diagram shows a comparison of the detection probabilities of incoherent detectors in Monte Carlo simulations for Swerling 0 and Swerling I targets, with different numbers of transmitting and receiving array elements. Figure 9 The curves showing the relationship between the detection probability of the incoherent detector and the signal-to-noise ratio difference for the target models Swerling 0 and Swerling I in three cases are shown when the product of the number of array elements is 12.

[0207] pass Figures 4 to 9 It can be concluded that: (1) The derived detection probability and false alarm probability are consistent with the simulation results; (2) The difference in signal-to-noise ratio between different platforms will affect the target detection performance. The greater the difference in signal-to-noise ratio, the better the detection performance; (3) The number of pulses will affect the target detection performance curve. The greater the number of pulses, the better the detection performance. However, the structural complexity of the radar hardware and the computational complexity of the software will increase accordingly. Therefore, the appropriate number of pulses should be selected according to the actual situation; (4) The detection probability is related to the number of transmitting array elements and receiving array elements. The greater the product of transmitting array elements and receiving array elements, the better the detection performance.

[0208] Figures 10 to 14 Simulation results for an approximate coherent detector are shown. Specifically, Figure 10The relationship between the detection probability of the approximately coherent detector and the signal-to-noise ratio difference is shown in the case of non-fluctuating targets. Figure 11 The comparison curves of detection probabilities in Monte Carlo simulations of two target models, Swerling type 0 and Swerling type I, for approximate coherent detectors are shown. Figure 12 The comparison curves of detection probability between Monte Carlo simulation and theoretical expression of an approximate coherent detector for non-fluctuating targets with different pulse numbers are shown. Figure 13 The diagram shows a comparison of the detection probabilities of the approximate coherent detector in Monte Carlo simulations for the target cases of Swerling 0 and Swerling I with different numbers of pulses. Figure 14 The diagram shows a comparison of the detection probabilities of the approximate coherent detector in Monte Carlo simulations for Swerling 0 and Swerling I targets, with different numbers of transmitting and receiving array elements.

[0209] Figures 15 to 19 Simulation results for a coherent detector are shown. Specifically, Figure 15 The curves showing the relationship between the detection probability of the coherent detector and the difference in signal-to-noise ratio are presented in the case of non-fluctuating targets. Figure 16 The comparison curves of detection probabilities from Monte Carlo simulations of coherent detectors for two target models, Swerling type 0 and Swerling type 1, are shown. Figure 17 The diagram shows a comparison of the detection probabilities of the coherent detector in Monte Carlo simulation and theoretical expression for non-fluctuating targets with different pulse numbers. The Monte Carlo simulation and theoretical expression of the approximate coherent detector and the coherent detector are compared when the pulse number K is 4, 8, 12 and 16 respectively. Figure 18 The diagram shows a comparison of the detection probabilities of the coherent detector in Monte Carlo simulations for the target cases of Swerling 0 and Swerling I with different numbers of pulses. Figure 19 The diagram shows a comparison of detection probabilities in Monte Carlo simulations of coherent detectors for Swerling 0 and Swerling I targets, with different numbers of transmitting and receiving array elements.

[0210] Based on the simulation results of the approximate coherent detector and the coherent detector, it can be concluded that: (1) the derived detection probability and false alarm probability are consistent with the simulation results; (2) the difference in signal-to-noise ratio between different platforms will affect the target detection performance. The greater the difference in signal-to-noise ratio, the better the detection performance; (3) the number of pulses will affect the target detection performance curve. The greater the number of pulses, the better the detection performance, but the structural complexity and computational complexity will increase accordingly. Therefore, the appropriate number of pulses should be selected according to the actual situation; (4) the detection probability is related to the number of transmitting and receiving array elements. When the product of the transmitting and receiving array elements is equal, the detection probability curves almost overlap; the greater the product of the transmitting and receiving array elements, the better the detection performance. (5) According to Figure 20 The diagram showing the relationship between the detection probability and signal-to-noise ratio of the approximate coherent detector and the coherent detector illustrates that the detection performance of the approximate coherent detector is slightly worse than that of the coherent detector, but it requires fewer known conditions and is easier to implement.

[0211] Figures 21 to 24 Simulation results for a hybrid detector are shown. Specifically, Figure 21 The curves showing the relationship between the detection probability of the hybrid detector and the difference in signal-to-noise ratio are illustrated in the case of non-fluctuating targets. Figure 22 The comparison curves of detection probabilities in Monte Carlo simulations of a hybrid detector using Swerling type 0 and Swerling type I target models are shown. Figure 23 The graph shows a comparison of the detection probabilities of the hybrid detector in Monte Carlo simulations for the target cases of Swerling 0 and Swerling I with different numbers of pulses. Figure 24 The diagram shows a comparison of detection probabilities in Monte Carlo simulations of a hybrid detector for Swerling 0 and Swerling I targets, with different numbers of transmitting and receiving array elements.

[0212] pass Figures 21 to 24 The results show that: (1) the derived detection probability and false alarm probability are consistent with the simulation results; (2) the difference in signal-to-noise ratio between different platforms will affect the target detection performance. The greater the difference in signal-to-noise ratio, the better the detection performance; (3) the number of pulses will affect the target detection performance curve. The greater the number of pulses, the better the detection performance. However, the structural complexity of the radar hardware and the computational complexity of the software will increase accordingly. Therefore, the appropriate number of pulses should be selected according to the actual situation; (4) the detection probability is related to the number of transmitting array elements and receiving array elements. When the product of the transmitting array elements and the receiving array elements is equal, the detection probability curves almost overlap. The greater the product of the transmitting array elements and the receiving array elements, the better the detection performance.

[0213] Furthermore, for the four detection methods in the embodiments of the present invention, see [link to documentation]. Figure 25 and Figure 26The graphs show the relationship between the detection probability and signal-to-noise ratio of the four detectors under non-undulating target conditions, and the comparison of the detection probabilities of the four detectors in Monte Carlo simulations under undulating target conditions. Figure 25 and Figure 26 It can be seen that, under the same parameters, the detection performance of the coherent detector is the best, followed by the near-coherent detector, the detection performance of the incoherent detector is the worst, and the detection performance of the hybrid detector is between that of the near-coherent detector and the incoherent detector.

[0214] Based on the same inventive concept as the aforementioned technical solution, see [link to inventive concept]. Figure 27 This invention illustrates a target detection method for a novel distributed MIMO radar system, applicable to the aforementioned novel distributed MIMO radar system. In this system, at least two transmitting platforms are distributed, each including at least two transmitting antennas; at least two receiving platforms are also distributed, each including at least two receiving antennas; in each transmitting or receiving platform, the distance between adjacent transmitting antennas or adjacent receiving antennas is half the wavelength of the radar wave emitted by the transmitting antenna. The method includes:

[0215] S2501: Transmitting radar transmitted wave signals with mutually orthogonal waveforms through each transmitting antenna of each transmitting platform, and receiving the received signal reflected by the radar transmitted wave signal from the detected target through each receiving antenna of each receiving platform.

[0216] S2502: Perform down-conversion sampling and matched filtering on the received signal to generate the transmit-receive-pulse vector of the received signal;

[0217] S2503: Based on the transmit-receive-pulse vector of the received signal, the target to be detected is detected by an incoherent detector, a coherent detector, an approximately coherent detector, or a hybrid detector.

[0218] It should be noted that the specific implementation methods, examples, and undescribed details of detecting the target using incoherent detectors, coherent detectors, near-coherent detectors, or hybrid detectors as described in S2503 can all be found in the description of the technical solution in the aforementioned new distributed MIMO radar system 1. This embodiment of the invention will not elaborate further on these details.

[0219] This application also provides a computer-readable storage medium storing at least one instruction, which is executed by a processor to implement the functions of each component in the novel distributed MIMO radar system described in the above embodiments, as well as the target detection method of the novel distributed MIMO radar.

[0220] This application also provides a computer program product, which includes computer instructions stored in a computer-readable storage medium; a processor of a computing device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computing device to perform the functions of each component in the novel distributed MIMO radar system and the target detection method of the novel distributed MIMO radar provided in various optional implementations of the above aspects.

[0221] Those skilled in the art will recognize that the functions described in the embodiments of this application in one or more of the above examples can be implemented using hardware, software, firmware, or any combination thereof. When implemented using software, these functions can be stored in a computer-readable medium or transmitted as one or more instructions or code on a computer-readable medium. Computer-readable media include computer storage media and communication media, wherein communication media include any medium that facilitates the transfer of a computer program from one place to another. Storage media can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0222] It should be noted that the technical solutions described in the embodiments of the present invention can be combined arbitrarily without conflict.

[0223] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A novel distributed multiple-input multiple-output (MIMO) radar system, characterized in that, The system includes: The system consists of at least two distributed transmission platforms, each of which includes at least two transmission antennas. The system comprises at least two receiving platforms in a distributed configuration, each receiving platform including at least two receiving antennas; in each transmitting or receiving platform, the distance between adjacent transmitting antennas or the distance between adjacent receiving antennas is half the wavelength of the radar wave emitted by the transmitting antenna. The control and analysis processing equipment is configured to: transmit radar transmitted wave signals with mutually orthogonal waveforms through each transmitting antenna of each transmitting platform, and receive the received signal reflected by the radar transmitted wave signal from the detected target through each receiving antenna of each receiving platform. Furthermore, the received signal is down-converted, sampled, and matched-filtered to generate a transmit-receive-pulse vector of the received signal, wherein the transmit-receive-pulse vector is constructed by performing a Kronecker product operation on the transmit steering vector, the receive steering vector, and the Doppler vector; Based on the transmit-receive-pulse vector of the received signal, the target is detected by a hybrid detector, wherein the hybrid detector performs coherent accumulation of the signal within the same receiving platform and incoherent accumulation between different receiving platforms; Through the first m The launch platform's first p Each transmitting antenna transmits radar wave signals. ,in, Indicates the complex baseband waveform. Indicates the carrier frequency. t Indicates time; Through the first n The first receiving platform q The receiving antenna receives the first m The target echo signal of all transmitting antennas on each transmitting platform is ,in, P m Indicates the first m The total number of transmitting antennas on each transmitting platform; , Indicates the detected target relative to the first m The launch platform and the first n Doppler frequency shift caused by relative motion between receiving platforms Indicates the first m The launch platform and the first n The relative speed of motion between the receiving platforms; , Indicates from the first m The launch platform's first p The transmitting antenna to the first n The first receiving platform q The delay of each receiving antenna, Indicates the first m The launch platform and the first n The angle between the line connecting the center of the elliptical detection area formed by the receiving platform and the target being detected, and the major axis of the elliptical detection area. k Indicates the pulse sequence number. Indicates the pulse repetition period; This represents the scattering coefficient of the target being detected; The received signals through each receiving antenna of each receiving platform include the target echo signal and the interference signal; The complex baseband waveform in the radar transmitted signal is sampled, and the target echo signal is down-converted to obtain the first... k The target echo signal of each pulse signal is: in, Let L represent the signal matrix of the m-th transmitting platform, and L represent the length of the transmitted signal. Indicates the launch steering vector. Indicates the receiving guide vector. and They represent and The p and the q One element, and They can be represented as: The wavelength of the transmitted waveform. c Represents the speed of light. This represents the total number of receiving antennas on the nth receiving platform. Indicates the first m The visible view from the launch platform to the target being detected. Indicates the first n The viewing angle from the receiving platform to the detected target; the first m The launch platform and the first n The receiving platform in the first k The Doppler vector during each pulse period is represented as: Using the sampled signal of the complex baseband waveform in the radar transmitted wave signal to analyze the first k The target echo signal of each pulse signal is subjected to matched filtering to obtain the transmit-receive-pulse vector of the target echo signal as follows: in, Indicates the Kronecker product. This represents the Doppler signal portion of the target echo signal. This represents the amplitude signal portion of the target echo signal; Based on the target echo signal's transmit-receive-pulse vector and interference signals The received signal is obtained as follows: .

2. The system according to claim 1, characterized in that, The detection area formed by each transmitting platform and each receiving platform is an elliptical region, and the foci of the elliptical region are the transmitting platform and the receiving platform that form the detection area, respectively.

3. The system according to claim 1, characterized in that, The control and analysis processing equipment is configured as follows: Based on the binary detection principle and the received signal, two hypothetical scenarios are constructed: the first hypothetical scenario is described as the received signal not including the target echo signal but only including the interference signal, and the second hypothetical scenario is described as the received signal including both the target echo signal and the interference signal, with the amplitude signal portion and the Doppler signal portion in the received signal treated as a whole. Based on the received signals from all receiving platforms, the first likelihood function and the second likelihood function corresponding to the first assumption and the second assumption respectively are obtained; The incoherent detector is obtained based on the first likelihood function and the second likelihood function; Based on the fact that incoherent detectors do not contain signal-to-noise ratio weighting coefficients, a first statistic for incoherent detection is obtained; The first statistic is compared with a set incoherent detector threshold. When the first statistic is greater than the threshold, it is determined that the detected target exists.

4. The system according to claim 1, characterized in that, The control and analysis processing equipment is configured as follows: Based on the binary detection principle and the received signal, two hypothetical scenarios are constructed: the first hypothetical scenario is described as the received signal not including the target echo signal but only including the interference signal, and the second hypothetical scenario is described as the received signal including both the target echo signal and the interference signal, with the amplitude signal part and the phase signal part of the received signal being separated. Based on the received signals from all receiving platforms, the third likelihood function and the fourth likelihood function corresponding to the first assumption and the second assumption respectively are obtained; The coherent detector is obtained based on the third and fourth likelihood functions; A second statistic for coherent detection is obtained based on the coherent detector; The second statistic is compared with a set coherent detector threshold. When the second statistic is greater than the threshold, it is determined that the detected target exists.

5. The system according to claim 4, characterized in that, The control and analysis processing equipment is configured as follows: Based on the second statistic used for coherent detection, a third statistic is obtained by reducing the amplitude information to perform near-coherent detection; The third statistic is compared with a set threshold for an approximate coherent detector. When the third statistic is greater than the threshold for an approximate coherent detector, it is determined that the detected target exists.

6. The system according to claim 1, characterized in that, The control and analysis processing equipment is configured as follows: Based on the binary detection principle and the received signal, two hypothetical scenarios are constructed: the first hypothetical scenario is described as the received signal not including the target echo signal but only including the interference signal, and the second hypothetical scenario is described as the received signal including both the target echo signal and the interference signal. Based on the received signals from all receiving platforms, the fifth likelihood function and the sixth likelihood function corresponding to the first assumption and the second assumption respectively are obtained; The hybrid detector is obtained based on the fifth and sixth likelihood functions; The signals from the hybrid detector are coherently accumulated within the same receiving platform and incoherently accumulated between different receiving platforms to obtain a fourth statistic for hybrid detection. The fourth statistic is compared with a set hybrid detector threshold. When the fourth statistic is greater than the threshold, it is determined that the detected target exists.

7. A target detection method for a novel distributed MIMO radar system, characterized in that, The target detection method of the novel distributed MIMO radar is applied to the novel distributed MIMO radar system according to any one of claims 1 to 6. In the novel distributed MIMO radar system, at least two transmitting platforms are distributed, each transmitting platform including at least two transmitting antennas; and at least two receiving platforms are distributed, each receiving platform including at least two receiving antennas. In each transmitting or receiving platform, the distance between adjacent transmitting antennas or the distance between adjacent receiving antennas is half the wavelength of the radar wave emitted by the transmitting antenna. The method includes: The radar transmit wave signals with mutually orthogonal waveforms are transmitted through each transmit antenna of each transmit platform, and the received signal reflected by the radar transmit wave signal after being detected is received through each receive antenna of each receive platform. Furthermore, the received signal is down-converted, sampled, and matched-filtered to generate a transmit-receive-pulse vector of the received signal, wherein the transmit-receive-pulse vector is constructed by performing a Kronecker product operation on the transmit steering vector, the receive steering vector, and the Doppler vector; Based on the transmit-receive-pulse vector of the received signal, the target is detected by a hybrid detector, wherein the hybrid detector performs coherent accumulation of the signal within the same receiving platform and incoherent accumulation between different receiving platforms; The transmission of mutually orthogonal radar transmitted wave signals through each transmitting antenna of each transmitting platform, and the reception of the radar transmitted wave signals reflected by the detected target through each receiving antenna of each receiving platform, include: Through the first m The launch platform's first p Each transmitting antenna transmits radar wave signals. ,in, Indicates the complex baseband waveform. Indicates the carrier frequency. t Indicates time; Through the first n The first receiving platform q The receiving antenna receives the first m The target echo signal of all transmitting antennas on each transmitting platform is ,in, P m Indicates the first m The total number of transmitting antennas on each transmitting platform; , Indicates the detected target relative to the first m The launch platform and the first n Doppler frequency shift caused by relative motion between receiving platforms Indicates the first m The launch platform and the first n The relative speed of motion between the receiving platforms; , Indicates from the first m The launch platform's first p The transmitting antenna to the first n The first receiving platform q The delay of each receiving antenna, Indicates the first m The launch platform and the first n The angle between the line connecting the center of the elliptical detection area formed by the receiving platform and the target being detected, and the major axis of the elliptical detection area. k Indicates the pulse sequence number. Indicates the pulse repetition period; This represents the scattering coefficient of the target being detected; The received signals through each receiving antenna of each receiving platform include the target echo signal and the interference signal; The complex baseband waveform in the radar transmitted signal is sampled, and the target echo signal is down-converted to obtain the first... k The target echo signal of each pulse signal is: in, Let L represent the signal matrix of the m-th transmitting platform, and L represent the length of the transmitted signal. Indicates the launch steering vector. Indicates the receiving guide vector. and They represent and The p and the q One element, and They can be represented as: The wavelength of the transmitted waveform. c Represents the speed of light. This represents the total number of receiving antennas on the nth receiving platform. Indicates the first m The visible view from the launch platform to the target being detected. Indicates the first n The viewing angle from the receiving platform to the detected target; the first m The launch platform and the first n The receiving platform in the first k The Doppler vector during each pulse period is represented as: The step of down-converting and sampling the received signal and performing matched filtering to generate the transmit-receive-pulse vector of the received signal includes: Using the sampled signal of the complex baseband waveform in the radar transmitted wave signal to analyze the first k The target echo signal of each pulse signal is subjected to matched filtering to obtain the transmit-receive-pulse vector of the target echo signal as follows: in, Indicates the Kronecker product. This represents the Doppler signal portion of the target echo signal. This represents the amplitude signal portion of the target echo signal; Based on the target echo signal's transmit-receive-pulse vector and interference signals The received signal is obtained as follows: .

8. A computer storage medium, characterized in that, The computer storage medium stores at least one instruction, which is executed by a processor to implement the functions of each component in the novel distributed MIMO radar system as described in any one of claims 1 to 6, or the target detection method of the novel distributed MIMO radar as described in claim 7.

Images