Airborne Radar Motion Velocity Estimation Method Based on Accumulation and Parallelization
An airborne radar and motion speed technology, applied in the direction of calculation, program control design, multi-program device, etc., can solve the problems of insufficient use of hardware computing units and slow computing speed, so as to improve the utilization rate of hardware resources, improve the cumulative and The effect of reducing operation speed and algorithm complexity
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Embodiment 1
[0022] During the imaging process of airborne synthetic aperture radar, due to the influence of airflow, the motion instability is very large. If motion compensation is not adopted, the recorded data will be greatly distorted due to the influence of unstable factors, which will reduce the imaging quality. Can't even image. Before motion compensation, the estimation of motion parameters is essential, and if the acceleration vector estimated in the previous stage is to be time-integrated to obtain the velocity vector for real-time imaging on the machine, fast accumulation and solution are required. However, the current accumulation and serial Row-solve methods fall short of this speed requirement. For this reason, the present invention is through innovation, proposes the airborne radar motion speed estimation method based on accumulation and parallelization, see figure 1 , including the following steps:
[0023] Step 1 Generate the motion acceleration vector of the airborne ra...
Embodiment 2
[0030] The airborne radar speed estimation method based on accumulation and parallelization is the same as embodiment 1, see figure 2 , figure 2 For the thread configuration schematic diagram of the GPU kernel function of the present invention, the process of the thread configuration of the design GPU kernel function described in step 2 includes:
[0031] 2a) Analysis of hardware resource capacity: limited by hardware resources, there is an upper limit on the number of thread blocks that can be opened up by the GPU and the size of each thread block. The maximum number of thread blocks that can be opened up by the GPU grid is GridMax. The maximum number of threads is BlockMax. In this example, GridMax=2147483647*65535*65535, BlockMax=1024.
[0032] 2b) Analyze the vector to be calculated, and determine the calculation principle: the length of the airborne radar motion acceleration vector A is l, l=2 n , n is a positive integer, calculation principle: in the calculation, ea...
Embodiment 3
[0039] The airborne radar speed estimation method based on accumulation and parallelization is the same as that in Embodiment 1-2, and the process of generating the airborne radar motion speed variation vector described in step 3 includes:
[0040] 3a) Allocate GPU shared memory: according to the thread configuration of the GPU kernel function, allocate GPU shared memory for each thread block, the size of the shared memory in each thread block is 2*BlockNum*sizeof(type), a total of GridNum thread blocks, type It is the data type of airborne radar motion parameters, and sizeof(type) indicates the byte length occupied by a variable of this data type. In this example, GridNum=16, BlockNum=1024, the data type of the radar motion parameter is single-precision floating point (float), and sizeof(type)=4.
[0041] 3b) Generate airborne radar motion velocity variation vector: Under the thread configuration of the GPU kernel function, according to the calculation principle in step 2, en...
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