A fast positioning method for ultra-sparse distributed arrays

Abstract

The present invention discloses a fast positioning method suitable for ultra-sparse distributed arrays, which mainly solves the target positioning problem of ultra-sparse distributed array radar systems. The implementation process is: constructing a "beam scanning range lookup table" to determine the distance range of a single beam scan under different azimuths and elevation angles; performing beam scanning on the airspace, preliminarily searching for the target position, and preliminarily determining the approximate direction of the target; reducing the search interval within a small range, and using direct positioning to accurately locate the target. Compared with traditional positioning methods, the present invention has lower complexity and better real-time performance.

Description

Technical Field

[0001] The invention relates to a rapid positioning method applicable to an ultra-sparse distributed array in the field of radar target positioning, and is particularly applicable to rapid positioning of a target by a wide-area ultra-sparse distributed array radar system. Background Art

[0002] Compared with a single radar system, a wide-area ultra-sparse distributed array radar system has a larger detection range and higher detection performance. At the same time, the collaborative and complementary working characteristics of each station enhance its anti-reconnaissance and anti-interference capabilities, and has gradually become an important direction for the development of current radar equipment. The wide-area ultra-sparse distributed array radar system consists of numerous transceiver nodes scattered over a square kilometer or even wider area, and each node contains a fixed number of transceiver array elements. Currently, distributed radar target positioning is mainly divided into two categories, one is two-step positioning, and the other is direct positioning. The two-step positioning method first estimates the transmission delay and other information of the target echo. In the second step, based on the measurement value of the first step, the equation group is constructed in combination with the prior position information of each radar to solve the target position. The algorithm is greatly affected by the signal-to-noise ratio, and there is an error in the delay estimation in the first step, and the positioning accuracy is low. Direct positioning directly uses the received signals of each radar to construct a cost function about the target, conducts a spatial search, calculates the cost function value at each search point, and directly estimates the target position through the maximum value of the cost function. This method makes the most of the received signal and avoids the error caused by the estimation delay in the two-step positioning method. The positioning accuracy is high, but the ultra-sparse distributed array has a wide distribution range, a large array aperture, and an extremely narrow main beam width. The algorithm requires a spatial search, which leads to high computational complexity and poor real-time performance. Summary of the invention

[0003] The object of the present invention is to avoid the deficiencies in the above-mentioned background technology and provide a fast positioning method suitable for ultra-sparse distributed arrays.

[0004] The technical solution adopted by the present invention is:

[0005] A fast positioning method applicable to an ultra-sparse distributed array comprises the following steps:

[0006] ① Determine the basic parameters of the ultra-sparse distributed array system, including the number of nodes and the number of array elements contained in each node, and select a node as a reference point, and mark the coordinates of any point P in the airspace as p = (α p ,β p ,R p ), α p ,β p ,R p Respectively represent the azimuth, elevation and distance relative to the reference point;

[0007] ② Divide the search range into independent search units in the spatial azimuth, elevation and distance dimensions, and calculate the power density w at each unit. p , take the same azimuth and elevation angle w p ≤3dB range corresponding to the distance unit [R min ,R max ] as the 3dB beam scanning distance range, and form a beam scanning range lookup table with the azimuth angle, elevation angle and corresponding 3dB beam scanning distance range at each unit;

[0008] ③ Roughly divide the search range in the spatial azimuth and elevation dimensions, with the division interval being greater than 10 times the 3dB beam width of the entire array. According to the azimuth and elevation angles of each unit relative to the reference point after division, find the corresponding 3dB beam scanning distance range in the beam scanning range lookup table [R min ,R max ], and then perform distance dimension search on each beam, that is, [R min ,R max ] Then divide it again, determine the distance of each divided unit relative to the reference point, and then calculate the distance from each divided unit to each node and the signal transmission delay. According to the obtained delay, delay and phase compensation are performed on the received signals of all nodes, and coherent accumulation is performed. The unit position corresponding to the peak value of the accumulated signal is the roughly estimated target position p';

[0009] ④ With p' as the center, re-divide the search area within a small range. The division intervals of the azimuth and elevation dimensions are not higher than the 3dB beam width of the array, and the division interval of the distance dimension is not higher than one distance resolution unit. Calculate the cost function at each unit position. The unit position with the largest cost function is the target position. Among them, the size of a distance resolution unit is c / (2*B), where c represents the speed of light and B represents the bandwidth of the transmitted signal.

[0010] At this point, fast positioning suitable for ultra-sparse distributed arrays is completed.

[0011] Compared with the background technology, the present invention has the following advantages:

[0012] The present invention is suitable for target positioning in the context of ultra-sparse distributed arrays. When performing spatial search, beam scanning is first used for a rough search, and the precise 3dB beam scanning distance range is determined according to the azimuth and elevation angles of the spatial division unit, thereby avoiding invalid searches of areas outside the beam detection range. After determining the approximate position of the target, the search range is re-established near the position, and direct positioning is used for precise search. The idea of ​​first a rough search and then a fine search is adopted, which greatly reduces the computational complexity and improves the real-time performance of the algorithm. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 It is a flow chart of a fast positioning method applicable to an ultra-sparse distributed array of the present invention. DETAILED DESCRIPTION

[0014] Reference Figure 1 , a fast positioning method applicable to an ultra-sparse distributed array in this embodiment, the specific implementation steps are as follows:

[0015] Step 1, determine the basic parameters of the ultra-sparse distributed array system: define the number of nodes contained in the system as M, the number of array elements contained in each node as N, and select a node as a reference point, and mark the coordinates of any point P in the airspace as p = (α p ,β p ,r p ), where α p ,β p ,R p Respectively represent the azimuth, elevation and distance relative to the reference point;

[0016] Step 2: Divide the search range into independent search units in the spatial azimuth, elevation, and distance dimensions, and calculate the power density w at each unit. p , take the same azimuth and elevation angle w p ≤3dB range corresponding to the distance unit [R min ,R max ] as the 3dB beam scanning distance range, and form a beam scanning range lookup table with the azimuth angle, elevation angle and corresponding 3dB beam scanning distance range at each unit;

[0017] Power density p The calculation formula is:

[0018] w p =20*log(|x p (t=0)| 2 );

[0019] Where log(·) means taking the logarithm, x p It represents the sum of the radiation signals of all transmitting elements in the array at any point P in space;

[0020] Step 3: beam scanning, perform a preliminary rough search for the target location: roughly divide the search range in the spatial azimuth and elevation dimensions, with the division interval being greater than 10 times the 3dB beam width of the entire array. According to the azimuth and elevation angles of each unit relative to the reference point after division, find the corresponding 3dB beam scanning distance range in the beam scanning range lookup table [R min ,R max ], and then perform distance dimension search on each beam, that is, [R min ,Rmax ] Then divide it again, determine the distance of each divided unit relative to the reference point, and then calculate the distance from each divided unit to each node and the signal transmission delay. According to the obtained delay, delay and phase compensation are performed on the received signals of all nodes, and coherent accumulation is performed. The unit position corresponding to the peak value of the accumulated signal is the roughly estimated target position p';

[0021] Step 4, accurately search the target position within a small range: take p' as the center, re-divide the search area within the set small range, the azimuth and elevation division intervals are not higher than the 3dB beam width of the array, and the distance division interval is not higher than one distance resolution unit, calculate the cost function at each unit position, and the unit position with the largest cost function is the target position; where the size of a distance resolution unit is c / (2*B), c represents the speed of light, and B represents the bandwidth of the transmitted signal;

[0022] The cost function is:

[0023]

[0024] Among them, Q represents the direct positioning cost function, r i (t),i=1,2,…M represents the signal of the ith node after delay and phase compensation, max(·) represents the maximum value, and ||·||2 represents the norm.

[0025] This completes the fast positioning for ultra-sparse distributed arrays.

Claims

1. A fast positioning method suitable for ultra-sparse distributed arrays, characterized in that , including the following steps: ① Determine the basic parameters of the ultra-sparse distributed array system, including the number of nodes and the number of array elements contained in each node, and select a node as a reference point, and mark the coordinates of any point P in the airspace as p = (α p ,β p ,R p ), α p ,β p ,R p Respectively represent the azimuth, elevation and distance relative to the reference point; ② Divide the search range into independent search units in the spatial azimuth, elevation and distance dimensions, and calculate the power density w at each unit. p , take the same azimuth and elevation angle w p ≤3dB range corresponding to the distance unit [R min ,R max ] as the 3dB beam scanning distance range, and form a beam scanning range lookup table with the azimuth angle, elevation angle and corresponding 3dB beam scanning distance range at each unit; Among them, the power density w p The calculation formula is: w p =20*log(|x p (t=0)| 2 ); In the formula, log(·) means taking the logarithm, x p It represents the sum of the radiation signals of all transmitting elements in the array at any point P in space; ③ Roughly divide the search range in the spatial azimuth and elevation dimensions, with the division interval being greater than 10 times the 3dB beam width of the entire array. According to the azimuth and elevation angles of each unit relative to the reference point after division, find the corresponding 3dB beam scanning distance range in the beam scanning range lookup table [R min ,R max ], and then perform distance dimension search on each beam, that is, [R min ,R max ] Then divide it again, determine the distance of each divided unit relative to the reference point, and then calculate the distance from each divided unit to each node and the signal transmission delay. According to the obtained delay, delay and phase compensation are performed on the received signals of all nodes, and coherent accumulation is performed. The unit position corresponding to the peak value of the accumulated signal is the roughly estimated target position p'; ④ With p' as the center, re-divide the search area within a small range. The division intervals of the azimuth and elevation dimensions are not higher than the 3dB beam width of the array, and the division interval of the distance dimension is not higher than one distance resolution unit. Calculate the cost function at each unit position. The unit position with the largest cost function is the target position. Among them, the size of a distance resolution unit is c / (2*B), where c represents the speed of light and B represents the bandwidth of the transmitted signal. Among them, the cost function is: Where Q represents the direct positioning cost function, r i (t), i = 1, 2, ... M represents the signal of the ith node after delay and phase compensation, max(·) represents the maximum value, ||·||2 represents the norm, and M represents the number of nodes; At this point, fast positioning suitable for ultra-sparse distributed arrays is completed.

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