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Constant false alarm detection method for automotive millimeter wave anti-collision radar based on autoregressive time series model

A time series model, constant false alarm detection technology, applied in the field of constant false alarm detection, can solve the problem of sacrificing the real-time performance of vehicle-mounted millimeter-wave radar system, achieve good applicable value, good accuracy and real-time performance, increase stability and reliability. The effect of reliability

Active Publication Date: 2017-10-27
DALIAN ROILAND SCI & TECH CO LTD
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] Many of the radar constant false alarm detection methods above are of great significance in theoretical research, but they sacrifice the real-time performance of the actual vehicle-mounted millimeter-wave radar system, an important indicator of the system.

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  • Constant false alarm detection method for automotive millimeter wave anti-collision radar based on autoregressive time series model

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Embodiment 1

[0024] A constant false alarm detection method for a vehicle-mounted millimeter-wave anti-collision radar based on an autoregressive time series model, comprising the following steps:

[0025] S1. The echo received by the millimeter wave radar signal, in N FFT Fast Fourier transform is performed on the points to get N in each time period FFT The value after the fast Fourier transform of the point, as a time series of each time period;

[0026] S2. For the current threshold time series Y n (t)(t≥4) and the time series Y of the first three time periods of the series n (t-1), Y n (t-2), Y n (t-3) Perform data update respectively, and obtain the new time series Y′ corresponding to the current threshold time series and the time series of the first three time periods of the series respectively n (t), Y' n (t-1), Y' n (t-2), Y' n (t-3).

[0027] S3. Calculate the mean value of the new time series corresponding to the time series of the first three time periods of the current...

Embodiment 2

[0032] The difference from Embodiment 1 is that the method also includes the following steps: S5. Obtaining the final threshold value Y n_mx :

[0033] Y n_mx =Y n_yz ×μ, μ is the threshold adjustment factor.

[0034] Since in embodiment 1, the calculated threshold may only be not much larger than the original data, it is easy to have a certain false alarm rate, so the threshold is increased by the threshold adjustment factor, which can effectively reduce the false alarm rate.

Embodiment 3

[0036] The method for updating the time series in step S2 in the above two embodiments is:

[0037] S2.1. Sort the current time series in ascending order and delete the maximum value Y of M percent of the series max_M％ (t) Or directly delete the M maximum values, and delete the minimum value Y of N percent of the sequences at the same time min_N％(t) Or directly delete the N minimum fingers, M represents the M maximum values ​​after the sorted sequence, and N represents the N minimum values ​​​​before the sorted sequence;

[0038] S2.2. Calculate the mean Y for all values ​​of the remaining time series Q (t);

[0039] S2.3. Use the calculated average value Y Q (t) Replace the deleted maximum and minimum values ​​to complete the update of the current time series.

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Abstract

The invention discloses a vehicle-mounted millimeter wave crashproof radar constant false alarm detection method based on an autoregression time sequence model, and belongs to the field of constant false alarm detection, for solving the problem of incapability of reserving real-time performance of a millimeter wave radar system by use of a conventional false alarm detection method. The main technical points are as follows: S1, carrying out rapid Fourier transformation on echoes received by millimeter wave radar signals; S2, respectively carrying out data updating on a current threshold time sequence and time sequences of previous three time periods of the sequence; S3, solving a mean value of a new time sequence corresponding to the time sequence of the previous three time periods of the current threshold time sequence on corresponding points; and S4, obtaining a threshold of a current period by use of the autoregression model. The method provided by the invention has the advantage of guaranteeing real-time performance of a system in a constant false alarm detection process.

Description

technical field [0001] The invention belongs to the field of constant false alarm detection and relates to a constant false alarm detection method for a vehicle-mounted millimeter wave anti-collision radar. Background technique [0002] With the high development of the modernization level, the traffic problem has become an urgent problem to be solved in various countries. The millimeter-wave car anti-collision radar is the best way to solve this kind of problem. The biggest advantage of the millimeter-wave car anti-collision radar is that it can work around the clock. Applied in the fields of automobiles and intelligent transportation. When the millimeter-wave automotive anti-collision radar works in a clutter environment, the threshold setting of the detector must be adaptive to the change of the clutter power level, so that the target detection caused by clutter, that is, the false alarm, can be kept at a certain level. A lower acceptable level, thus solving the shortcomin...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01S13/93G01S7/41
CPCG01S7/41G01S13/931
Inventor 田雨农王鑫照周秀田史文虎
Owner DALIAN ROILAND SCI & TECH CO LTD
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