A method for evaluating performance of air surveillance radar based on SNR estimation and track report

Abstract

The application provides a kind of air monitoring radar performance evaluation method based on SNR estimation and track report. The echo signal of radar target, the transmitting signal, and the track report of the aircraft are collected; the minimum mean square error estimation of echo amplitude is calculated according to the echo signal and the transmitting signal, and the echo signal-to-noise ratio SNR is calculated; the radar performance index parameter is calculated according to the echo signal-to-noise ratio SNR and the index mathematical model of the radar performance index and the echo signal-to-noise ratio SNR; the track report of the aircraft is analyzed according to the radar performance index parameter, the track quality and the track quality are determined, and the radar performance is further evaluated. Compared with the prior art, the mathematical model of the signal-to-noise ratio and the radar maximum effective distance, the measurement accuracy and the detection probability performance index is established, the track report statistics analysis is carried out, the performance index and the track quality are obtained, and the radar performance comprehensive evaluation is further carried out based on the above index.

Description

Technical Field

[0001] This invention relates to the field of radar system evaluation technology, and more specifically, to a method for evaluating the performance of air surveillance radar based on SNR estimation and point-track reporting. Background Technology

[0002] The design and implementation of radar systems are both aimed at fulfilling their missions and achieving their performance goals. Currently, the evaluation of radar performance indicators is usually conducted externally using instruments or special experiments. While such evaluations are accurate and reliable, they require specialized measurement facilities and personnel to measure at appropriate times and locations, followed by analysis and calculation. This results in high costs, long processing times, and an inability to obtain the radar's current performance in real time. If, during radar operation, the collected data, intermediate results of radar signal processing, and generated messages could be analyzed and calculated in real time using the radar's internal resources or by adding auxiliary measurement modules, a performance model could be established, evaluation methods could be proposed, and key performance indicators could be calculated online. This would allow for the automatic perception of the radar's real-time performance at a lower cost. The real-time performance perception can then be fed back to the radar's control system, allowing for resource reallocation, hardware and software reconfiguration, and parameter adjustments to ensure the radar's performance meets expectations and adapts to the operating environment.

[0003] The detection performance of an air surveillance radar is mainly reflected in: the radar's effective range; the probability of target detection; the accuracy of measurement; and the quality of output point and track data. During radar operation, echo signals and target point and track data output after radar processing can be observed. If radar performance can be evaluated in real time from internal signals and data, the radar system's resources can be allocated to match the radar's power, aperture, spectrum, time, and space usage to the current mission. Furthermore, the difference between real-time performance and design performance reflects the health status of the radar system. Summary of the Invention

[0004] In view of this, the purpose of this invention is to provide a method for real-time evaluation of the performance indicators of an air-to-air radar from within the radar itself during operation, thereby facilitating subsequent adjustments and fault feedback information for the radar.

[0005] This invention provides a method for evaluating the performance of air surveillance radar based on SNR estimation and point-track reporting, the method comprising:

[0006] Step 1: Collect radar target echo signals, transmitted signals, and aircraft spot track reports;

[0007] Step 2: Calculate the minimum mean square error estimate of the echo amplitude based on the echo signal and the transmitted signal, and calculate the echo signal-to-noise ratio (SNR).

[0008] Step 3: Calculate the radar performance index parameters based on the echo signal-to-noise ratio (SNR) and the mathematical model of radar performance index and echo SNR.

[0009] Step 4: Analyze the aircraft's spot track report based on the radar performance index parameters to determine the spot quality and track quality.

[0010] Step 5: Evaluate radar performance based on the radar performance parameters calculated in Step 3 and the spot quality and track quality determined in Step 4.

[0011] Furthermore, in step 1, the echo signal is represented as:

[0012] x(t)=As(t-τ)+n(t)

[0013] Where A is the echo amplitude, τ is the echo delay, s(t-τ) is the transmitted signal waveform with an echo delay of τ, and n(t) is Gaussian white noise with unknown power.

[0014] Furthermore, step 2 also includes calculating the mean square error of the echo signal x(t) and As(t-τ). Represented as:

[0015]

[0016] In the formula R xs (τ) represents the cross-correlation between the echo and the transmitted signal, and E represents the expected value. To minimize the mean square error... Minimum, that is Taking the derivative of A as 0, we obtain the estimated echo amplitude. for:

[0017]

[0018] Furthermore, the echo signal power is expressed as: Noise power is expressed as: The signal-to-noise ratio is expressed as:

[0019] Furthermore, step 4 also includes:

[0020] Calculate the total number of detections M during the statistical period based on the radar parameters. i The number of times the target was detected, N i Obtain the statistical detection probability P. di , is represented as:

[0021]

[0022] During periods without a target, count the number of false alarms F. iThe false alarm rate P was obtained. fai , is represented as:

[0023]

[0024] Determine the point quality index and the track quality characteristic index; the point quality index includes range spread, azimuth spread, and number of convergent points; the track quality index includes track maintenance, track fragmentation, and short track rate.

[0025] Point quality = range spread × bearing spread × number of points of convergence; track quality = track maintenance rate - track fragmentation - short track rate.

[0026] Furthermore, step 5 also includes:

[0027] For each radar performance indicator, spot quality, and track quality, corresponding feedback thresholds and fault thresholds are set.

[0028] If the radar performance indicators, spot quality, or track quality exceed the corresponding feedback threshold, control information is output, indicating that the radar resources need to be scheduled.

[0029] If the radar performance indicators, spot quality, or track quality exceed the corresponding fault threshold, a fault message will be output, indicating that the radar needs to be repaired.

[0030] In this invention, the echo signal and transmitted signal of the radar target, as well as the aircraft's spot track report, are collected. The minimum mean square error estimate of the echo amplitude is calculated based on the echo signal and transmitted signal, and the echo signal-to-noise ratio (SNR) is calculated. Radar performance parameters are calculated based on the echo SNR and a mathematical model relating radar performance indicators to the echo SNR. Data analysis of the aircraft's spot track report is performed based on the radar performance parameters to determine the spot quality and track quality. Finally, radar performance is evaluated based on the calculated radar performance parameters and the determined spot quality and track quality. Compared to existing technologies, this approach first establishes a mathematical model for performance indicators such as signal-to-noise ratio (SNR) and radar maximum operating range, measurement accuracy, and detection probability. The SNR is then estimated online using echoes and the model. This SNR is then substituted into the mathematical model to calculate the indicator values. Furthermore, statistical analysis of point track reports yields performance indicators and point track quality. Finally, a comprehensive radar performance evaluation method based on these performance indicators is proposed. When a single indicator changes or the overall performance indicator exceeds a preset threshold, feedback information is output as a real-time sensing result. This allows the radar resource management module to reallocate resources based on the evaluation results to adapt to the environment and can also be used for radar fault diagnosis. Attached Figure Description

[0031] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0032] Figure 1 This invention discloses a method for evaluating the performance of air surveillance radar based on SNR estimation and point-track reporting.

[0033] Figure 2 This is a graph showing the relationship between different distances and detection probabilities disclosed in the embodiments of the present invention;

[0034] Figure 3 This is a schematic diagram of the velocity measurement accuracy of pulse Doppler processing disclosed in an embodiment of the present invention;

[0035] Figure 4 This is a flowchart of the overall implementation of the present invention. Detailed Implementation

[0036] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided to make this application more comprehensive and complete, and to fully convey the concept of the exemplary embodiments to those skilled in the art.

[0037] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough understanding of embodiments of this application. However, those skilled in the art will recognize that the technical solutions of this application can be practiced without one or more of the specific details, or other methods, components, apparatuses, steps, etc., can be employed. In other instances, well-known methods, apparatuses, implementations, or operations are not shown or described in detail to avoid obscuring various aspects of this application.

[0038] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0039] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0040] It should be noted that "multiple" as mentioned in this article refers to two or more.

[0041] The implementation details of the technical solutions in the embodiments of this application are described in detail below:

[0042] Air surveillance radar is a type of radar used to search for, monitor, and identify aerial targets and determine their coordinates and motion parameters.

[0043] This embodiment establishes a relationship model between radar performance indicators such as range, measurement accuracy, detection probability, spot quality, and track quality, and the signal-to-noise ratio (SNR) and spot / track reports. It proposes an SNR estimation method based on the minimum mean square error estimation method to estimate the SNR from the radar echo. Then, the performance indicators are calculated using the relationship model between the performance indicators and the SNR. Other performance indicators are calculated from the spot / track reports using statistical analysis. Finally, the radar performance is evaluated based on these indicators, and the results are fed back to the radar control module and the fault diagnosis module.

[0044] This embodiment proposes a performance evaluation method for air surveillance radar based on SNR estimation and point-track reporting. The method includes:

[0045] Step S1: Collect the radar target's echo signal, transmitted signal, and aircraft's point track report.

[0046] Specifically, in this embodiment, process data acquisition is performed first. Multiple radar target echo pulse data are acquired; guided by ADS-B data, the point track reports of specific civil aviation aircraft flights are acquired.

[0047] Step S1 requires collecting point track reports of aircraft for specific flights. Based on civil aviation flight plans, select a subset of aircraft falling within the detection range during the test period. Obtain the aircraft's longitude, latitude, and altitude information from the real-time aircraft position map provided by an ADS-B website (e.g., https: / / zh.flightaware.com). Calculate the aircraft's azimuth and slant range relative to the radar from its radar position. Based on the known target azimuth and slant range, collect point track reports for statistical analysis of the matched targets.

[0048] Furthermore, in step 1, the echo signal is represented as:

[0049] x(t)=As(t-τ)+n(t)

[0050] Where A is the echo amplitude, τ is the echo delay, s(t-τ) is the transmitted signal waveform with an echo delay of τ, and n(t) is Gaussian white noise with unknown power.

[0051] Furthermore, step 1 also includes: collecting the aircraft's point track report based on the guidance of ADS-B data;

[0052] Based on the latitude and longitude position in ADS-B, convert it to the ECEF coordinate system position. The conversion method is as follows:

[0053]

[0054] a = Earth's semi-major axis = 6,378,137.0 m; e 2 =Square of the first eccentricity = 6.69437999014 × 10 -3 φ = latitude; λ = longitude; h = altitude; (X,Y,Z) represents the aircraft's position in the ECEF coordinate system.

[0055] Step S2: Calculate the minimum mean square error estimate of the echo amplitude based on the echo signal and the transmitted signal, and calculate the echo signal-to-noise ratio (SNR).

[0056] Specifically, in this embodiment, the SNR (Signal to Noise Ratio) is further estimated. The minimum mean square error estimate of the echo amplitude is calculated using the transmitted pulse and the echo pulse; the echo signal power, noise power, and signal-to-noise ratio are calculated.

[0057] Furthermore, step 2 also includes calculating the mean square error of the echo signal x(t) and As(t-τ). Represented as:

[0058]

[0059] In the formula R xs (τ) represents the cross-correlation between the echo and the transmitted signal, and E represents the expected value. To minimize the mean square error... Minimum, that is Taking the derivative of A as 0, we obtain the estimated echo amplitude. for:

[0060]

[0061] Furthermore, the echo signal power is expressed as: Noise power is expressed as: The signal-to-noise ratio is expressed as:

[0062] Step S3: Calculate the radar performance index parameters based on the echo signal-to-noise ratio (SNR) and the mathematical model of radar performance index and echo SNR.

[0063] Specifically, in this embodiment, step S3 involves calculating key radar performance indicators. Based on the relationship between radar performance indicators and signal-to-noise ratio (SNR), the estimated average SNR of multiple echo pulses is input into the indicator mathematical model to calculate the indicator values.

[0064] In step 3, the radar performance indicators include maximum operating range, ranging accuracy, direction finding accuracy, velocity measurement accuracy, and detection probability. Based on the relationship between SNR and these indicators, the point track reports are calculated separately.

[0065] Furthermore, the radar performance indicators include detection probability, maximum effective range, ranging accuracy, direction finding accuracy, and velocity measurement accuracy;

[0066] Step 3 involves calculating radar performance parameters based on the echo signal-to-noise ratio (SNR) and the mathematical model relating radar performance indicators to SNR, including:

[0067] (1) Under Gaussian white noise, the detection probability P d The mathematical model is expressed as:

[0068]

[0069] Where Q is the Marcum Q function, SNR is the radar echo signal-to-noise ratio, and P fa This represents the probability of a false alarm.

[0070] (2) The mathematical model for the maximum effective distance is expressed as:

[0071]

[0072] Among them, P t λ is the radar's transmit power (W); G is the radar antenna gain; λ is the radar wavelength (m); σ is the target's effective reflective area; k is the Boltzmann constant (taken as 1.38 × 10⁻⁶). 23 T0 is the standard temperature (290K); B is the receiving channel bandwidth (Hz); F is the receiving channel noise figure (S / N). omin Minimum detectable signal-to-noise ratio;

[0073] (3) The mathematical model for ranging accuracy is expressed as:

[0074] Radar ranging measures the time delay of the echo signal. For pulse signals, the time delay estimation accuracy is:

[0075]

[0076] B rms This refers to the root mean square bandwidth or effective bandwidth.

[0077]

[0078] Where S(f) is the Fourier transform of the signal, and the ranging accuracy σ can be obtained from the time delay estimation accuracy. R , where c is the speed of light;

[0079]

[0080] (4) The mathematical model for radar direction finding accuracy is expressed as:

[0081]

[0082] Where E is the received signal energy; N0 is the noise power spectral density; λ is the radar signal wavelength; and γ is the effective aperture width, determined by the antenna aperture field distribution. When the aperture field has a uniform amplitude distribution... Where d is the antenna aperture;

[0083] When the aperture field has a cosine distribution, γ 2 =1.28d 2 Direction finding accuracy σ θ Represented as:

[0084] (5) Mathematical model for radar velocity measurement accuracy, including: determining velocity measurement accuracy using pulse Doppler processing; velocity measurement accuracy σ using pulse Doppler processing. v , is represented as:

[0085]

[0086] Radar velocity measurement typically employs pulse Doppler processing, such as... Figure 3 The diagram shown illustrates the velocity measurement accuracy of the pulse Doppler processing in this embodiment. The echo signal data is arranged into a matrix in the fast and slow time domains. L is the number of range units within the pulse repetition period, M is the number of pulses processed by pulse Doppler, λ is the radar signal wavelength, and PRF represents the pulse repetition frequency.

[0087] Step S4: Analyze the aircraft's spot track report based on the radar performance index parameters to determine the spot quality and track quality.

[0088] Furthermore, step 4 also includes calculating the total number of detections M during the statistical period based on the radar parameters. i The number of times the target was detected, N i Obtain the statistical detection probability P. di , is represented as:

[0089]

[0090] During periods without a target, count the number of false alarms F. i The false alarm rate P was obtained. fai , is represented as:

[0091]

[0092] In this embodiment, range broadening, azimuth broadening, and number of convergence points are proposed as indicators of track quality, and the product of track features is proposed to represent track quality. Track maintenance, track fragmentation, and short track rate are proposed as track quality features, and the sum and difference results calculated from track features are proposed to represent track quality.

[0093] The quality indicators of point tracks and the quality characteristics of flight tracks are determined. The quality indicators of point tracks include distance spread, azimuth spread, and number of convergent points. The quality indicators of flight tracks include flight track maintenance, flight track fragmentation, and short flight track rate.

[0094] Point quality = range spread × bearing spread × number of points of convergence; track quality = track maintenance rate - track fragmentation - short track rate.

[0095] Specifically, in step 4, several characteristic indicators are proposed based on the point track report to evaluate the point quality and track quality.

[0096] After detecting and determining a target, the radar outputs a point trace of the target. This point trace contains the target's position and velocity information, as well as information about false targets. Point targets with low relative resolution appear as a single point on the radar display. Targets with higher relative resolution may appear as multiple points, but these do not constitute a range image or a real aperture image. In this case, point trace processing is needed to eliminate false targets and merge multiple points of a single target together, a process known as point trace aggregation. During point trace aggregation, the features of the point trace are extracted simultaneously. Point trace features include:

[0097] (1) Widening the distance

[0098] Range broadening is the difference between the farthest and nearest range cells of a target point. The range broadening characteristic is related to the radar's range resolution; the higher the radar's range resolution, the greater the difference in range broadening characteristics between the target and clutter. The range broadening for a point target is:

[0099] Range widening = (farthest distance cell - nearest distance cell) × range resolution

[0100] (2) Axial expansion

[0101] Azimuth spread is the difference between the maximum and minimum azimuth of a target point. The maximum azimuth spread can be calculated based on the antenna beamwidth and the number of radar pulses accumulated. When the azimuth spread exceeds this value, it is considered a singular point.

[0102] Azimuth widening = (maximum azimuth - minimum azimuth) × beamwidth

[0103] (3) Number of condensation points

[0104] The number of aggregation points refers to the number of detection points that aggregate the target trace, i.e., the number of traces falling within the gate. If the number of aggregation points in the clutter is too small, or if the number of aggregation points constituting the trace is too low, the trace is considered a false trace.

[0105] The overall quality of a dot is represented as the product of three terms: Dot quality = Distance broadening × Azimuth broadening × Number of cohesive points;

[0106] The following indicators are proposed for evaluating track quality:

[0107] (1) Track maintenance rate

[0108] This feature measures the continuity of a flight path, obtained by statistically analyzing the proportion of paths that continuously lose a certain number of points. The track maintenance rate is the percentage of paths that continuously lose no more than 4 points within 90% of the radar's maximum detection range.

[0109] (2) Fragmentation of flight path

[0110] Track fragmentation is the average number of tracks obtained from a target. The radar track report outputs the total number of targets m and the number of tracks n within the current detection range, and the track fragmentation is represented by n / m.

[0111] (3) Short track rate

[0112] The short track rate refers to the proportion of tracks consisting of 1-5 points, which can be obtained by counting the number of columns in the track information matrix.

[0113] Track quality is a combination of three indicators: a higher track maintenance rate is better, and a lower track fragmentation and short track rate are better. Therefore, track quality is defined as:

[0114] Track quality = Track maintenance rate - Track fragmentation - Short track rate.

[0115] Step S5: Evaluate radar performance based on the radar performance index parameters calculated in step S3 and the spot quality and track quality determined in step S4.

[0116] Specifically, in this embodiment, corresponding feedback thresholds and fault thresholds are set for each radar performance indicator, spot quality, and track quality. If the radar performance indicator, spot quality, or track quality exceeds the corresponding feedback threshold, control information is output, indicating that the radar resources need to be scheduled. If the radar performance indicator, spot quality, or track quality exceeds the corresponding fault threshold, fault information is output, indicating that the radar needs to be repaired.

[0117] Furthermore, in step 5, the performance of the radar system is evaluated using a threshold method. For each preset radar indicator, a separate threshold is set. The spot quality indicator is the product of three spot features, and the track quality indicator is the sum and difference of three track features. Each performance indicator (maximum effective range, ranging accuracy, direction finding accuracy, velocity accuracy, detection probability, spot quality, and track quality) corresponds to two thresholds: one is a fault threshold, which indicates a system malfunction if the measured indicator value is worse than the fault threshold, and outputs a fault warning; the other is a feedback threshold, which provides control information if the indicator is between the fault threshold and the feedback threshold; if the indicator is better than the feedback threshold, the system performance is good.

[0118] In the actual evaluation calculation, step 3 involves calculating the radar's key performance indicators based on the SNR and point track information estimated in step 2. The ranging accuracy σ can be obtained from the signal-to-noise ratio (SNR) and the mathematical model. R Direction finding accuracy σ θ and speed measurement accuracy σ v For the maximum effective range, one approach is to estimate based on the signal-to-noise ratio (SNR): As can be seen from the mathematical model of the detection probability, under a constant false alarm probability, the detection probability is determined by the SNR. When the false alarm probability is fixed, the SNR that gives a 50% detection probability can be directly found. 0.5 The corresponding maximum detection range is:

[0119]

[0120] Among them, R max R is the maximum detection range of the radar, R is the measured target distance, and SNR is the measured signal-to-noise ratio of the target echo signal. 0.5 This is the signal-to-noise ratio corresponding to a detection probability of 50% when the false alarm probability is constant.

[0121] In step 4, point-track reports of specific civil flights are collected, and the data of the point-track reports are analyzed to obtain the radar detection range. As the target moves from far to near or from near to far, multiple measurements are taken at regular intervals, and the number of detections, the number of times the target is detected, and the detection distance are recorded as shown in Table 1.

[0122] Table 1. Number of times the target was detected and the distance at the time of detection.

[0123]

[0124] Based on the number of detections and the number of times the target was detected, the detection probability is calculated:

[0125]

[0126] Similarly, in the absence of a target, by counting the number of detections M and the number of times a target was detected F, the false alarm probability is:

[0127]

[0128] When a sufficient number of messages are collected, the total detection probability and false alarm probability are:

[0129] Based on the point track reports, the maximum effective range of the radar can also be estimated. The probability of radar detection of a specific target is correlated with the target distance, as shown in the table above. A graph depicting the relationship between different distances and detection probabilities can then be drawn. Figure 2 The diagram shows the relationship between different distances and detection probabilities in this embodiment. A threshold for the probability of detection is selected; values ​​below this threshold are considered to exceed the radar's detection range. For example, the target distance R' with a detection probability of 50% is selected. max As an indicator for measuring the detection range of radar.

[0130] In step 5, the current performance of the radar system is comprehensively evaluated based on the maximum effective range, ranging accuracy, direction finding accuracy, velocity measurement accuracy, detection probability, spot quality, and track quality, and feedback thresholds and fault thresholds are set. If the performance indicators exceed the feedback thresholds, control information is output, indicating that the radar resources need to be rescheduled; if the performance indicators exceed the fault thresholds, fault information is output, indicating that the radar needs maintenance.

[0131] Furthermore, this embodiment also proposes a comprehensive evaluation method: First, single-indicator evaluation. If any of the seven indicators (maximum effective range, ranging accuracy, direction finding accuracy, velocity accuracy, detection probability, spot quality, and track quality) significantly deviates from expectations, feedback or fault information is issued. The threshold for a single indicator can be set with a relatively large value, such as a 50% change. Second, comprehensive performance evaluation, which is a weighted sum of the changes in the seven indicators, with a threshold set for the sum. The weights depend on the radar system's function; for example, if the focus is on search function, the weight of detection probability is increased; if the focus is on measurement function, the weight of accuracy is increased; if the focus is on tracking function, the weights of spot and track quality are increased. That is:

[0132] Overall performance variation = Maximum effective distance variation ratio * ω1 + Ranging accuracy variation ratio * ω2 + Direction finding accuracy variation ratio * ω3 + Velocity accuracy variation ratio * ω4 + Detection probability variation ratio * ω5 + Point quality variation ratio * ω6 + Track quality variation ratio * ω7.

[0133] In this embodiment, as Figure 4 The diagram shows the overall implementation flowchart of this embodiment. By acquiring echo pulses, transmitted pulses, and point track reports, and performing minimum mean square error estimation on the echo pulses and transmitted pulses, the echo signal-to-noise ratio is further calculated. Based on the index mathematical model, the radar's power range, measurement accuracy, and detection probability are detected. Specifically, the power range is described by the maximum effective range, and the measurement accuracy is described by ranging accuracy, direction-finding accuracy, and velocity measurement accuracy. Point track quality and track quality are generated based on the point track reports. The current performance of the radar system is comprehensively evaluated based on the maximum effective range, ranging accuracy, direction-finding accuracy, velocity measurement accuracy, detection probability, point track quality, and track quality. Based on the evaluated radar performance, control and fault diagnosis are then performed.

[0134] Compared to existing technologies, this approach first establishes a mathematical model for performance indicators such as signal-to-noise ratio (SNR) and radar maximum operating range, measurement accuracy, and detection probability. The SNR is then estimated online using echoes and the model. This SNR is then substituted into the mathematical model to calculate the indicator values. Furthermore, statistical analysis of point track reports yields performance indicators and point track quality. Finally, a comprehensive radar performance evaluation method based on these performance indicators is proposed. When a single indicator changes or the overall performance indicator exceeds a preset threshold, feedback information is output as a real-time sensing result. This allows the radar resource management module to reallocate resources based on the evaluation results to adapt to the environment and can also be used for radar fault diagnosis.

[0135] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0136] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices or units, or may be electrical, mechanical or other forms of connection.

[0137] The units described as separate components may or may not be physically separate. As will be appreciated by those skilled in the art, the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0138] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0139] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or grid device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0140] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for evaluating the performance of air surveillance radar based on SNR estimation and point-track reporting, characterized in that, The method includes: Step 1: Collect radar target echo signals, transmitted signals, and aircraft spot track reports; Step 2: Calculate the minimum mean square error estimate of the echo amplitude based on the echo signal and the transmitted signal, and calculate the echo signal-to-noise ratio (SNR). Step 3: Calculate the radar performance index parameters based on the echo signal-to-noise ratio (SNR) and the mathematical model of radar performance index and echo SNR. Step 4: Analyze the aircraft's spot track report based on the radar performance index parameters to determine the spot quality and track quality. Step 5: Evaluate radar performance based on the radar performance index parameters calculated in Step 3 and the spot quality and track quality determined in Step 4. In step 1, the echo signal is represented as follows: in, Echo amplitude, For echo delay, For having The transmitted signal waveform with echo delay. The power is unknown Gaussian white noise; Step 2 also includes calculating the echo signal. and mean square error , is represented as: In the formula This indicates the cross-correlation between the echo and the transmitted signal, where E represents the expected value. To minimize the mean square error... Minimum, that is Taking the derivative of A as 0, we obtain the estimated echo amplitude. for: Furthermore, the echo signal power is expressed as: Noise power is expressed as: The signal-to-noise ratio is expressed as: ; Among them, the radar performance indicators in step 3 include maximum effective range, ranging accuracy, direction finding accuracy, velocity measurement accuracy, and detection probability. Based on the relationship between SNR and the indicators, the point track reports are calculated respectively. Based on the aforementioned echo signal-to-noise ratio (SNR) and the mathematical model relating radar performance indicators to SNR, radar performance parameters are calculated, including: (1) Detection probability under Gaussian white noise The mathematical model is expressed as: Where Q is the Marcum Q function and SNR is the radar echo signal-to-noise ratio. Indicates the probability of a false alarm; (2) The mathematical model for the maximum effective distance is expressed as: in, G represents the radar's transmit power; G represents the radar antenna gain. The radar wavelength; The effective reflective area of ​​the target is denoted by k; k is the Boltzmann constant. B is the standard temperature; F is the receiving channel bandwidth; F is the receiving channel noise figure. This represents the minimum detectable signal-to-noise ratio.

2. The air surveillance radar performance evaluation method based on SNR estimation and point-track reporting as described in claim 1, characterized in that, Step 4 also includes: Calculate the total number of detections during the statistical period based on radar parameters. Number of times the target was detected , obtain the statistical detection probability , is represented as: During periods without a target, count the number of false alarms. Resulting in the false alarm rate , is represented as: The point quality index and the track quality characteristic index are determined; the point quality index includes range spread, azimuth spread, and number of convergent points; the track quality characteristic index includes track maintenance, track fragmentation, and short track rate. Point quality = Distance spread × Azimuth spread × Number of points of convergence; Track quality = Track maintenance rate - Track fragmentation - Short track rate.

3. The air surveillance radar performance evaluation method based on SNR estimation and point-track reporting as described in claim 2, characterized in that, Step 5 further includes: For each radar performance indicator, spot quality, and track quality, corresponding feedback thresholds and fault thresholds are set. If the radar performance indicators, spot quality, or track quality exceed the corresponding feedback threshold, control information is output, indicating that the radar resources need to be scheduled. If the radar performance indicators, spot quality, or track quality exceed the corresponding fault threshold, a fault message will be output, indicating that the radar needs to be repaired.

Images