ADS-B Site Location Selection Method for Civil Aviation Multilateration

Abstract

The present invention discloses a method for selecting the location of ADS-B stations for civil aviation multi-point positioning. Based on the historical flight ADS-B trajectory data of flights on air routes, the signal arrival time from the aircraft to each station is obtained through inversion calculation, and then the MLAT solution algorithm is used to obtain the calculated position coordinates of the aircraft; the ADS-B position coordinates and the calculated position coordinates of the aircraft are compared, and the calculation error is obtained; with the optimal position of the station as the goal, the station position is obtained through multiple iterative calculations, and at the same time, according to the preset random deviation, the position wandering direction angle is updated; the optimal position of the current station is obtained, and this position is used as the optimal position of the ADS-B station to be deployed. The present invention can effectively optimize the selection of the station position along a specific path. Only through several iterative processes, the accuracy of the multi-point positioning algorithm can be increased by ten to one hundred times.

Description

Technical Field

[0001] The present invention relates to the technical field of aircraft positioning and tracking, and particularly to a method for selecting the location of an ADS-B station for civil aviation multilateration. Background Art

[0002] Air traffic flow has experienced explosive growth in the past decade. To avoid aviation accidents and even collisions in such a high-density airspace, a consensus has been formed worldwide on using ATM (Air Traffic Management) technology and rules to divide aircraft by altitude and distance; that is, comprehensively applying ATS (Air Traffic Service), ASM (Air Space Management), and ATFM (Air Traffic Flow Management) to achieve the safe operation of aircraft. The key technology for achieving airspace division and collision avoidance lies in the ability to continuously locate and track all aircraft in the air. Traditional aircraft positioning and tracking technologies rely on radar systems, mainly including primary air traffic control radar and secondary radar. However, due to the limitation of the radar's operating range, its effectiveness in transoceanic and remote area flights is greatly reduced.

[0003] To achieve the goal of tracking and monitoring aircraft, especially flights, globally, the ITU (International Telecommunications Union) has reached a consensus on using ADS-B (Automatic Dependent Surveillance-Broadcast) information to implement a sky-air-ground integrated positioning and tracking system. On the other hand, to achieve the goal of a future large-capacity sky-air-ground integrated communication network, there is also an urgent need for high-precision real-time aircraft positioning and tracking technology.

[0004] Given the characteristics and challenges of a single ADS-B system, combined with the evolution of aircraft tracking and monitoring technology, solutions can be sought in the direction of multi-device and collaborative working modes. The multilateration (MLAT) system is precisely considered in this context. MLAT can use the same ADS-B broadcast signals received by multiple ground stations to estimate the track information of the target aircraft by capturing signal-level characteristics without demodulating the ADS-B message. Since the MLAT method does not rely on demodulated message information and multiple (more than 3) ground station receivers are redundant with each other, it can theoretically improve the positioning accuracy and the anti-interference ability of the system.

[0005] In a multi-lateration system, the location distribution of ground receiver stations has an important impact on the positioning accuracy of the MLAT algorithm. There is an optimal position for the ground stations, and optimization deployment is required. Taking the complexity of system design and deployment as an example, when the MLAT algorithm requires at least five stations to cooperate to complete position calculation and decision-making, if the planar position space is considered as a grid with a spacing of 500m on a 1000km×1000km plane, the size of the solution space is 10 33 orders of magnitude and cannot be obtained by brute-force exhaustive search. Summary of the Invention

[0006] The object of the present invention is to provide an ADS-B station location selection method for civil aviation multi-lateration, which can effectively optimize the selection of station locations along a specific path, reduce the number of iterations, and improve the accuracy of the multi-lateration algorithm.

[0007] To achieve the above object, the present invention provides the following technical solutions: An ADS-B station location selection method for civil aviation multi-lateration, including the following steps:

[0008] S1. Based on the historical flight ADS-B trajectory data of flights on the airway, using the ADS-B position coordinates of the aircraft trajectory and initializing the positions of N ADS-B stations to be deployed, inversely calculate the signal arrival time of the aircraft to each station;

[0009] S2. Using the signal arrival time of the aircraft to each station, calculate the arrival time difference of the aircraft to the remaining N-1 stations, and use the MLAT solution algorithm based on TDOA. Taking the arrival time differences of the N-1 stations as inputs, obtain the calculated position coordinates of the aircraft; compare the ADS-B position coordinates and the calculated position coordinates of the aircraft, and calculate the calculation error;

[0010] S3. Taking the optimal position of the station as the target, based on the station positions and calculation errors of the previous iteration of the MLAT solution algorithm based on TDOA in step S2, preset the station movement step size and the range of change of the position wandering direction angle, move each of the N stations respectively to obtain N movement schemes, then calculate the positions of the aircraft of the N movement schemes and the corresponding N calculation errors, and take the minimum value of the N calculation errors as the calculation error of this iteration;

[0011] S4. Compare the calculation error of this iteration with the calculation error of the previous iteration, take the station position corresponding to the smaller calculation error as the station position of the current iteration, and at the same time update the position wandering direction angle according to the preset random deviation; then return to execute step S3 until the preset maximum number of iterations is reached, obtain the optimal position of the current station, and take this position as the optimal position of the ADS-B station to be deployed.

[0012] Further, in the foregoing step S3, the variation range of the position wandering direction angle is not greater than π / N - 1.

[0013] Step S3 is specifically as follows: Based on the site position (S_pos_last_x, S_pos_last_y) and the solution error of the previous iteration, a preset site movement step size step and a variation range adt of the position wandering direction angle are set, and the site is tried to be moved respectively as follows:

[0014] S_pos_try_x = S_pos_last_x + step * cos(Angle_now),

[0015] S_pos_try_y = S_pos_last_y + step * sin(Angle_now), where Angle_now is the position wandering direction angle.

[0016] Further, in the foregoing step S4, the preset random deviation range is: greater than or equal to -π / N - 1 and less than or equal to π / N - 1.

[0017] Further, in the foregoing step S4, updating the position wandering direction angle includes the following steps:

[0018] S4.1. Compare the solution error of this iteration with the solution error of the previous iteration. If the solution error of this iteration is smaller, then execute step S4.2; otherwise, execute step S4.3;

[0019] S4.2. On the basis of the previous position wandering direction angle, add a random deviation, and use the added result as the updated position wandering direction angle;

[0020] S4.3. On the basis of the previous position wandering direction angle, add a random deviation, and then add the angle π for large-angle reversal, and use the added result of the three as the updated position wandering direction angle.

[0021] Further, in the foregoing step S4.2, on the basis of the previous position wandering direction angle, add a random deviation, and use the added result as the updated position wandering direction angle, as follows:

[0022] Angle_now = Angle_last + adt·(2rand - 1),

[0023] where rand is a random number between [0, 1].

[0024] Further, in the aforementioned step S4.3, based on the previous position wandering direction angle, a random deviation is added, and then a large-angle reversal is performed by adding the angle π. The sum of the three is used as the updated position wandering direction angle, as shown in the following formula:

[0025] Angle_now = Angle_last + adt·(2rand - 1) + π,

[0026] where rand is a random number between [0, 1].

[0027] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0028] 1. Before building a new ADS-B site, by collecting and analyzing historical ADS-B data, the construction location of the proposed new site can be evaluated and optimized to determine the best location, improving the accuracy and reliability of multi-point positioning of aircraft in the airway scenario.

[0029] 2. Compared with the existing site screening method, the iterative optimization method adopted by this method has a fast convergence speed, avoiding the computational complexity of brute-force solution.

[0030] 3. This method is applicable to different multi-point positioning algorithms and can be flexibly embedded into the existing multi-point positioning algorithm module to provide an optimal reference site scheme for the multi-point positioning algorithm.

[0031] 4. This method can help reduce the pre-analysis and decision-making costs, as well as reduce manpower and material resources, for improving the intelligent level of air traffic management construction. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 is a flowchart of the method of the present invention.

[0033] Figure 2 is a comparison result diagram of the aircraft tracking trajectory errors before and after the site location optimization. In the figure, (a) is the aircraft tracking trajectory diagram before the site optimization, and (b) is the aircraft tracking trajectory diagram after the site optimization. DETAILED DESCRIPTION OF THE INVENTION

[0034] In order to better understand the technical content of the present invention, specific embodiments are given below in conjunction with the accompanying drawings for illustration.

[0035] Aspects of the present invention are described with reference to the accompanying drawings, in which a number of illustrative embodiments are shown. Embodiments of the present invention are not limited to those described in the drawings. It should be understood that the present invention can be implemented by any one of the various concepts and embodiments introduced above, as well as the concepts and embodiments described in detail below, because the concepts and embodiments disclosed in the present invention are not limited to any particular embodiment. Additionally, some aspects disclosed in the present invention can be used alone or in any suitable combination with other aspects disclosed in the present invention.

[0036] As Figure 1 shown, the flowchart of the present invention for the method of selecting ADS-B site locations for civil aviation multi-point positioning includes the following steps:

[0037] S1. Select a certain civil aviation route as the optimization object, and obtain a large amount of historical flight ADS-B trajectory data on this route; based on the historical flight ADS-B trajectory data of the route, initialize the positions of 5 ADS-B sites to be deployed, and use the ADS-B position coordinates of the aircraft trajectory and the positions of the 5 ADS-B sites to be deployed to inversely calculate and obtain the signal arrival times of the aircraft at each site.

[0038] S2. Use the signal arrival times of the aircraft at each site to calculate the arrival time differences of the aircraft at the remaining 4 sites, and use the MLAT solution algorithm based on TDOA. With the arrival time differences of the 4 sites as the input, obtain the solved position coordinates of the aircraft; compare the ADS-B position coordinates and the solved position coordinates of the aircraft, and calculate the solved error; S3. With the optimal position of the site as the goal, based on the site position (S_pos_last_x, S_pos_last_y) and the solved error of the previous iteration of the MLAT solution algorithm based on TDOA, preset the site movement step size step and the range of change of the position wandering direction angle adt, and this range is not greater than π / 4. Then, attempt to move each of the 5 sites respectively, and the attempted positions are:

[0039] S_pos_try_x = S_pos_last_x + step * cos(Angle_now),

[0040] S_pos_try_y = S_pos_last_y + step * sin(Angle_now), where Angle_now is the position wandering direction angle.

[0041] Obtain 5 movement schemes, then solve the positions of the aircraft for the 5 schemes and the corresponding 5 solved errors, and use the minimum value among the 5 solved errors as the solved error for this iteration.

[0042] S4. Compare the solution error of this iteration with that of the last iteration, and use the site position corresponding to the smaller solution error as the site position of the current iteration. At the same time, according to a preset random deviation, the range of this random deviation is: greater than or equal to -π / 4 and less than or equal to π / 4. Then update the position wandering direction angle, and the specific update method is as follows:

[0043] S4.1. Compare the solution error of this iteration with that of the previous iteration. If the solution error of this iteration is smaller, then execute step S4.2; otherwise, execute step S4.3;

[0044] S4.2. Add a random deviation to the previous wandering direction angle, and use the added result as the updated position wandering direction angle, that is

[0045] Angle_now = Angle_last + adt·(2rand - 1)

[0046] where rand is a random number between [0, 1];

[0047] S4.3. Add a random deviation to the previous position wandering direction angle, and then add the angle π for large-angle inversion. Use the added result of the three as the updated position wandering direction angle, that is

[0048] Angle_now = Angle_last + adt·(2rand - 1) + π

[0049] where rand is a random number between [0, 1].

[0050] Based on obtaining the solution error, the new site position, and the new position wandering direction angle of this iteration cycle, then return to execute step S3 until the preset maximum number of iterations is reached, obtain the optimal position of the current site, and use this position as the optimal position of the ADS-B site to be deployed. As Figure 2 shown in the comparison result diagram of the aircraft tracking trajectory error before and after the site position optimization of the present invention, Figure 2 in which (a) is the aircraft tracking trajectory diagram before site optimization, and (b) is the aircraft tracking trajectory diagram after site optimization. Through the method of the present invention, the best site selection position is determined, and the accuracy and reliability of multi-point positioning of aircraft in the airway scenario are improved.

[0051] Although the present invention has been described above with preferred embodiments, it is not intended to limit the present invention. Those with ordinary knowledge in the technical field to which the present invention belongs can make various changes and modifications without departing from the spirit and scope of the present invention. Therefore, the protection scope of the present invention shall be subject to what is defined by the claims.

Claims

1. An ADS-B site location selection method for civil aviation multi-point positioning, characterized in that It includes the following steps: S1. Based on the historical flight ADS-B trajectory data of the airway, using the ADS-B position coordinates of the aircraft trajectory and the initialized positions of N ADS-B sites to be deployed, the signal arrival time from the aircraft to each site is obtained through inversion calculation; S2. Using the signal arrival time from the aircraft to each site, calculate the arrival time difference from the aircraft to the remaining N-1 sites. Using the MLAT solution algorithm based on TDOA, with the arrival time differences of the N-1 sites as the input, obtain the solved position coordinates of the aircraft; compare the ADS-B position coordinates and the solved position coordinates of the aircraft, and calculate the solved error; S3. Taking the optimal position of the site as the goal, based on the site position and the solved error of the previous iteration of the MLAT solution algorithm of TDOA in step S2, preset the site movement step size and the range of change of the position wandering direction angle, move each of the N sites respectively to obtain N movement schemes, then solve the positions of the aircraft of the N movement schemes and the corresponding N solved errors, and take the minimum value among the N solved errors as the solved error of this iteration; S4. Compare the solved error of this iteration and the solved error of the previous iteration, take the site position corresponding to the smaller solved error as the site position of the current iteration, and at the same time update the position wandering direction angle according to the preset random deviation; then return to execute step S3 until the preset maximum number of iterations is reached, obtain the optimal position of the current site, and take this position as the optimal position of the ADS-B site to be deployed.

2. The method for selecting the ADS-B site location for civil aviation multi-point positioning according to claim 1, wherein, In step S3, the range of change of the position wandering direction angle is not greater than π / (N-1).

3. The method for selecting the location of an ADS-B station for civil aviation multi-point positioning according to claim 1, wherein Step S3 is specifically: based on the site position (S_pos_last_x, S_pos_last_y) and the solved error of the previous iteration, preset the site movement step size step and the range of change of the position wandering direction angle adt, and try to move the sites respectively, as shown in the following formula: S_pos_try_x = S_pos_last_x + step * cos(Angle_now), S_pos_try_y = S_pos_last_y + step * sin(Angle_now), where Angle_now is the position wandering direction angle.

4. The method for selecting the position of an ADS-B station for civil aviation multi-point positioning according to claim 1, characterized in that In step S4, the preset random deviation range is: greater than or equal to -π / (N-1) and less than or equal to π / (N-1).

5. The method for selecting the location of an ADS-B station for civil aviation multi-point positioning according to claim 4, wherein In step S4, updating the position wandering direction angle includes the following steps: S4.

1. Compare the solved error of this iteration and the solved error of the previous iteration. If the solved error of this iteration is smaller, execute step S4.2, otherwise execute step S4.3; S4.

2. Add a random deviation to the previous position wandering direction angle, and take the added result as the updated position wandering direction angle; S4.

3. Add a random deviation to the previous position wandering direction angle, and then add the angle π for large-angle reversal, and take the sum of the three as the updated position wandering direction angle.

6. The method for selecting the location of an ADS-B station for civil aviation multi-point positioning according to claim 5, wherein In step S4.2, based on the previous position wandering direction angle, add a random deviation, and use the sum as the updated position wandering direction angle, as shown in the following formula: Angle_now = Angle_last + adt·(2rand - 1), where rand is a random number between [0, 1].

7. The method for selecting the ADS-B station location for civil aviation multi-point positioning according to claim 6, wherein In step S4.3, based on the previous position wandering direction angle, add a random deviation, and then add the angle π for large-angle inversion. Use the sum of the three as the updated position wandering direction angle, as shown in the following formula: Angle_now = Angle_last + adt·(2rand - 1) + π, where rand is a random number between [0, 1].

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